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  • 251.
    de Fréin, Ruairí
    et al.
    Sparse Signal Processing Group, University College Dublin.
    Rickard, Scott
    Sparse Signal Processing Group, University College Dublin.
    The Synchronized Short-Time-Fourier-Transform: Properties and Definitions for Multichannel Source Separation2011In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, ISSN 1053-587X, Vol. 59, no 1, p. 91-103Article in journal (Refereed)
    Abstract [en]

    This paper proposes the use of a synchronized linear transform, the synchronized short-time-Fourier-transform (sSTFT), for time-frequency analysis of anechoic mixtures. We address the short comings of the commonly used time-frequency linear transform in multichannel settings, namely the classical short-time-Fourier-transform (cSTFT). We propose a series of desirable properties for the linear transform used in a multichannel source separation scenario: stationary invertibility, relative delay, relative attenuation, and finally delay invariant relative windowed-disjoint orthogonality (DIRWDO). Multisensor source separation techniques which operate in the time-frequency domain, have an inherent error unless consideration is given to the multichannel properties proposed in this paper. The sSTFT preserves these relationships for multichannel data. The crucial innovation of the sSTFT is to locally synchronize the analysis to the observations as opposed to a global clock. Improvement in separation performance can be achieved because assumed properties of the time-frequency transform are satisfied when it is appropriately synchronized. Numerical experiments show the sSTFT improves instantaneous subsample relative parameter estimation in low noise conditions and achieves good synthesis.

  • 252.
    de Fréin, Ruairí
    et al.
    Sparse Signal Processing Group, University College Dublin, Dublin, Ireland.
    Rickard, Scott
    Sparse Signal Processing Group, University College Dublin, Dublin, Ireland.
    The Vibrato And Phoneme Rating Tool: A Real-Time Speech Therapy Feed- back Tool2005In: 3rd European Medical and Biological Engineering Conference, Prague, 2005, p. 1-4Conference paper (Refereed)
  • 253.
    de Fréin, Ruairí
    et al.
    Complex and Adaptive Systems Laboratory, University College Dublin, Ireland.
    Rickard, Scott
    Complex and Adaptive Systems Laboratory, University College Dublin, Ireland.
    Drakakis, Konstantinos
    Complex and Adaptive Systems Laboratory, University College Dublin, Ireland.
    Extracting Garch Effects from Asset Returns Using Robust NMF2009In: Digital Signal Processing Workshop and 5th IEEE Signal Processing Education Workshop, 2009. DSP/SPE 2009. IEEE 13th, Marco Island, FL: IEEE Signal Processing Society, 2009, p. 200-5Conference paper (Refereed)
    Abstract [en]

    Identification of assets on the stock market that exhibit co-movement is a critical task for generating an efficiently diversified portfolio. We present a new application of non-negative matrix factorization to factor analysis of financial time series. We consider a conditionally heteroscedastic latent factor model, where each series is parameterized by a univariate ARCH model. Volatility clustering characteristics, e.g. GARCH effects, of the constituent assets of the Dow Jones Industrial Average are lever-aged to cluster assets based on the commonality of their volatility clusters. We present a new non-negative matrix factorization algorithm which is robust in the presence of noise, Robust NMF. We use a mixed low-rank over-complete dictionary learning approach to separate out the background Gaussian noise, emphasize the GARCH effects and achieve clearer asset groupings.

  • 254.
    de Fréin, Ruairí
    et al.
    University College Dublin.
    Rickard, Scott T.
    University College Dublin.
    Pearlmutter, Barak A.
    National University of Ireland Maynooth.
    Constructing Time-Frequency Dictionaries for Source Separation via Time-Frequency Masking and Source Localisation2009In: Independent Component Analysis and Signal Separation / [ed] Tulay Adali et al.,, Brazil: Springer-Verlag New York, 2009, Vol. 5441, p. 573-580Conference paper (Refereed)
    Abstract [en]

    We describe a new localisation and source separation algo- rithm which is based upon the accurate construction of time-frequency spatial signatures. We present a technique for constructing time-frequency spatial signatures with the required accuracy. This algorithm for multi- channel source separation and localisation allows arbitrary placement of microphones yet achieves good performance. We demonstrate the efficacy of the technique using source location estimates and compare estimated time-frequency masks with the ideal 0 dB mask.

  • 255.
    de Fréin, Ruairí
    et al.
    University College Dublin, Ireland.
    Rickard, Scott T.
    Pearlmutter, Barak A.
    Sparse Multichannel Source Localization and Separation2008In: / [ed] The Institute of Mathematics and its Applications, Cirencester: The Institute of Mathematics and its Applications , 2008, p. 90-93Conference paper (Refereed)
    Abstract [en]

    The DUET and DESPRIT blind source separation algorithms attempt to recover J sources from I mixtures of these sources, in the interesting case where J > I, with minimal information about the mixing environment of underling sources statistics. We present a semi-blind generalization of the DUET-DESCRIPT approach which allows arbitary placement of the sensors and demixes the sources given the room impulse response. We learn a sparse representation of the mixtures on an over-complete spatial signatures dictionary. We localize and separate the constituent sources via binary masking of a power weighted histogram in location space or in attenuation-delay space. We demonstrate the robustness of this technique using synthetic room experiments.

  • 256.
    de Fréin, Ruairí
    et al.
    Waterford Institute of Technology, Ireland.
    Xu, Biao
    Waterford Institute of Technology, Ireland.
    Robson, Eric
    Waterford Institute of Technology, Ireland.
    Distributed Formal Concept Analysis Algorithms Based on an Iterative MapReduce Framework2012In: Lecture Notes in Computer Science, ISSN 0302-9743, E-ISSN 1611-3349, Vol. 7278, p. 292-308Article in journal (Refereed)
    Abstract [en]

    While many existing formal concept analysis algorithms are efficient, they are typically unsuitable for distributed implementation. Taking the MapReduce (MR) framework as our inspiration we introduce a distributed approach for performing formal concept mining. Our method has its novelty in that we use a light-weight MapReduce runtime called Twister which is better suited to iterative algorithms than recent distributed approaches. First, we describe the theoretical foundations underpinning our distributed formal concept analysis approach. Second, we provide a representative exemplar of how a classic centralized algorithm can be implemented in a distributed fashion using our methodology: we modify Ganter’s classic algorithm by introducing a family of MR⋆ algorithms, namely MRGanter and MRGanter+ where the prefix denotes the algorithm’s lineage. To evaluate the factors that impact distributed algorithm performance, we compare our MR∗ algorithms with the state-of-the-art. Experiments conducted on real datasets demonstrate that MRGanter+ is efficient, scalable and an appealing algorithm for distributed problems.

  • 257.
    De Vito, Luca
    et al.
    Department of Engineering, University of Sannio, 82100 Benevento, Italy.
    Lundin, Henrik
    KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre. KTH, School of Electrical Engineering (EES), Signal Processing.
    Rapuano, Sergio
    Department of Engineering, University of Sannio, 82100 Benevento, Italy.
    Bayesian calibration of a lookup table for ADC error correction2007In: IEEE Transactions on Instrumentation and Measurement, ISSN 0018-9456, E-ISSN 1557-9662, Vol. 56, no 3, p. 873-878Article in journal (Refereed)
    Abstract [en]

    This paper presents a new method for the correction of nonlinearity errors in analog-to-digital converters (ADCs). The method has been designed to allow a self-calibration in systems where an internal signal can be generated, such as base stations for mobile communications. The method has been implemented and tested in simulation on the behavioral model of commercial ADCs and on a hardware setup composed by a data acquisition board and a distorting circuit.

  • 258.
    del Aguila Pla, Pol
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Inverse problems in signal processing: Functional optimization, parameter estimation and machine learning2019Doctoral thesis, comprehensive summary (Other academic)
    Abstract [en]

    Inverse problems arise in any scientific endeavor. Indeed, it is seldom the case that our senses or basic instruments, i.e., the data, provide the answer we seek. It is only by using our understanding of how the world has generated the data, i.e., a model, that we can hope to infer what the data imply. Solving an inverse problem is, simply put, using a model to retrieve the information we seek from the data.

    In signal processing, systems are engineered to generate, process, or transmit signals, i.e., indexed data, in order to achieve some goal. The goal of a specific system could be to use an observed signal and its model to solve an inverse problem. However, the goal could also be to generate a signal so that it reveals a parameter to investigation by inverse problems. Inverse problems and signal processing overlap substantially, and rely on the same set of concepts and tools. This thesis lies at the intersection between them, and presents results in modeling, optimization, statistics, machine learning, biomedical imaging and automatic control.

    The novel scientific content of this thesis is contained in its seven composing publications, which are reproduced in Part II. In five of these, which are mostly motivated by a biomedical imaging application, a set of related optimization and machine learning approaches to source localization under diffusion and convolutional coding models are presented. These are included in Publications A, B, E, F and G, which also include contributions to the modeling and simulation of a specific family of image-based immunoassays. Publication C presents the analysis of a system for clock synchronization between two nodes connected by a channel, which is a problem of utmost relevance in automatic control. The system exploits a specific node design to generate a signal that enables the estimation of the synchronization parameters. In the analysis, substantial contributions to the identifiability of sawtooth signal models under different conditions are made. Finally, Publication D brings to light and proves results that have been largely overlooked by the signal processing community and characterize the information that quantized linear models contain about their location and scale parameters.

  • 259.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Calderero, F.
    Marqués, F.
    Marcello, J.
    Eugenio, F.
    Fast generation of LULC maps for temporal studies in North-Western Africa2014In: Geoscience and Remote Sensing Symposium (IGARSS), 2014 IEEE International / [ed] IEEE International, IEEE conference proceedings, 2014, p. 4280-4283Conference paper (Refereed)
    Abstract [en]

    This paper provides an objective evaluation of six supervised classification techniques and three state of the art features, with the objective of obtaining a single combination of them that provides both robustness and objective performance improvements. As a conclusion, a simple procedure for obtaining LULC maps with four targeted classes is proposed.

  • 260.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Cell detection by functional inverse diffusion and non-negative group sparsity – Part I: Modeling and Inverse Problems2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 20, p. 5407-5421Article in journal (Refereed)
    Abstract [en]

    In this two-part paper, we present a novel framework and methodology to analyze data from certain image-based biochemical assays, e.g., ELISPOT and Fluorospot assays. In this first part, we start by presenting a physical partial differential equations (PDE) model up to image acquisition for these biochemical assays. Then, we use the PDEs' Green function to derive a novel parametrization of the acquired images. This parametrization allows us to propose a functional optimization problem to address inverse diffusion. In particular, we propose a non-negative group-sparsity regularized optimization problem with the goal of localizing and characterizing the biological cells involved in the said assays. We continue by proposing a suitable discretization scheme that enables both the generation of synthetic data and implementable algorithms to address inverse diffusion. We end Part I by providing a preliminary comparison between the results of our methodology and an expert human labeler on real data. Part II is devoted to providing an accelerated proximal gradient algorithm to solve the proposed problem and to the empirical validation of our methodology.

  • 261.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Cell detection by functional inverse diffusion and non-negative group sparsity – Part II: Proximal optimization and Performance evaluation2018In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 20, p. 5422-5437Article in journal (Refereed)
    Abstract [en]

    In this two-part paper, we present a novel framework and methodology to analyze data from certain image-based biochemical assays, e.g., ELISPOT and Fluorospot assays. In this second part, we focus on our algorithmic contributions. We provide an algorithm for functional inverse diffusion that solves the variational problem we posed in Part I. As part of the derivation of this algorithm, we present the proximal operator for the non-negative group-sparsity regularizer, which is a novel result that is of interest in itself, also in comparison to previous results on the proximal operator of a sum of functions. We then present a discretized approximated implementation of our algorithm and evaluate it both in terms of operational cell-detection metrics and in terms of distributional optimal-transport metrics.

  • 262.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Cell detection on image-based immunoassays2018In: 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018), IEEE, 2018, p. 431-435Conference paper (Refereed)
    Abstract [en]

    Cell detection and counting in the image-based ELISPOT and Fluorospot immunoassays is considered a bottleneck.The task has remained hard to automatize, and biomedical researchers often have to rely on results that are not accurate.Previously proposed solutions are heuristic, and data-based solutions are subject to a lack of objective ground truth data. In this paper, we analyze a partial differential equations model for ELISPOT, Fluorospot, and assays of similar design. This leads us to a mathematical observation model forthe images generated by these assays. We use this model to motivate a methodology for cell detection. Finally, we provide a real-data example that suggests that this cell detection methodology and a human expert perform comparably.

  • 263.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Convolutional group-sparse coding and source localization2018Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a new interpretation of non-negatively constrained convolutional coding problems as blind deconvolution problems with spatially variant point spread function. In this light, we propose an optimization framework that generalizes our previous work on non-negative group sparsity for convolutional models. We then link these concepts to source localization problems that arise in scientific imaging, and provide a visual example on an image derived from data captured by the Hubble telescope.

  • 264.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Inferences from quantized data - Likelihood logconcavityManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper, we present to the signal processing community the most general likelihood logconcavity statement for quantized data to date, together with its proof, which has never been published. In particular, we show how Prékopa’s theorem can be used to show that the likelihood for quantized linear models is jointly logconcave with respect to both its location and scale parameter in a broad range of cases. In order to show this result and explain the limitations of the proof technique, we study sets generated by combinations of points with positive semi-definite matrices whose sum is the identity.

  • 265.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Pellaco, Lissy
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Dwivedi, Satyam
    Ericsson Research.
    Händel, Peter
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Clock synchronization over networks - Identifiability of the sawtooth modelManuscript (preprint) (Other academic)
    Abstract [en]

    In this paper, we analyze the two-node joint clocksynchronization and ranging problem. We focus on the case of nodes that employ time-to-digital converters to determine the range between them precisely. This specific design leads to a sawtooth model for the captured signal, which has not been studied in detail before from an estimation theory standpoint. In the study of this model, we recover the basic conclusion of a well-known article by Freris, Graham, and Kumar in clock synchronization. Additionally, we discover a surprising identifiability result on the sawtooth signal model: noise improves the theoretical condition of the estimation of the phase and offset parameters. To complete our study, we provide performance references for joint clock synchronization and ranging. In particular, we present the Cramér-Rao lower bounds that correspond to a linearization of our model, as well as a simulation study on the practical performance of basic estimation strategies under realistic parameters. With these performance references, we enable further research in estimation strategies using the sawtooth model and pave the path towards industrial use.

  • 266.
    del Aguila Pla, Pol
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Saxena, Vidit
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    Jaldén, Joakim
    KTH, School of Electrical Engineering and Computer Science (EECS), Information Science and Engineering.
    SpotNet – Learned iterations for cell detection in image-based immunoassays2019Conference paper (Refereed)
    Abstract [en]

    Accurate cell detection and counting in the image-based ELISpot and FluoroSpot immunoassays is a challenging task. Recently proposed methodology matches human accuracy by leveraging knowledge of the underlying physical process of these assays and using proximal optimization methods to solve an inverse problem. Nonetheless, thousands of computationally expensive iterations are often needed to reach a near-optimal solution. In this paper, we exploit the structure of the iterations to design a parameterized computation graph, SpotNet, that learns the patterns embedded within several training images and their respective cell information. Further, we compare SpotNet to a convolutional neural network layout customized for cell detection. We show empirical evidence that, while both designs obtain a detection performance on synthetic data far beyond that of a human expert, SpotNet is easier to train and obtains better estimates of particle secretion for each cell.

  • 267. Demisse, G. G.
    et al.
    Aouada, D.
    Ottersten, Björn
    Univesity of Luxembourg.
    Deformation Based Curved Shape Representation2018In: IEEE Transaction on Pattern Analysis and Machine Intelligence, ISSN 0162-8828, E-ISSN 1939-3539, Vol. 40, no 6, p. 1338-1351Article in journal (Refereed)
    Abstract [en]

    n this paper, we introduce a deformation based representation space for curved shapes in R-n. Given an ordered set of points sampled from a curved shape, the proposed method represents the set as an element of a finite dimensional matrix Lie group. Variation due to scale and location are filtered in a preprocessing stage, while shapes that vary only in rotation are identified by an equivalence relationship. The use of a finite dimensional matrix Lie group leads to a similarity metric with an explicit geodesic solution. Subsequently, we discuss some of the properties of the metric and its relationship with a deformation by least action. Furthermore, invariance to reparametrization or estimation of point correspondence between shapes is formulated as an estimation of sampling function. Thereafter, two possible approaches are presented to solve the point correspondence estimation problem. Finally, we propose an adaptation of k-means clustering for shape analysis in the proposed representation space. Experimental results show that the proposed representation is robust to uninformative cues, e.g., local shape perturbation and displacement. In comparison to state of the art methods, it achieves a high precision on the Swedish and the Flavia leaf datasets and a comparable result on MPEG-7, Kimia99 and Kimia216 datasets.

  • 268. Demisse, Girum G.
    et al.
    Aouada, Djamila
    Ottersten, Björn
    University of Luxemburg.
    Deformation-Based 3D Facial Expression Representation2018In: ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP), ISSN 1551-6857, E-ISSN 1551-6865, Vol. 14, no 1s, p. 17-1Article in journal (Refereed)
    Abstract [en]

    We propose a deformation-based representation for analyzing expressions fromthree-dimensional (3D) faces. A point cloud of a 3D face is decomposed into an ordered deformable set of curves that start from a fixed point. Subsequently, a mapping function is defined to identify the set of curves with an element of a high-dimensional matrix Lie group, specifically the direct product of SE(3). Representing 3D faces as an element of a high-dimensional Lie group has two main advantages. First, using the group structure, facial expressions can be decoupled from a neutral face. Second, an underlying non-linear facial expression manifold can be captured with the Lie group and mapped to a linear space, Lie algebra of the group. This opens up the possibility of classifying facial expressions with linear models without compromising the underlying manifold. Alternatively, linear combinations of linearised facial expressions can be mapped back from the Lie algebra to the Lie group. The approach is tested on the Binghamton University 3D Facial Expression (BU-3DFE) and the Bosphorus datasets. The results show that the proposed approach performed comparably, on the BU-3DFE dataset, without using features or extensive landmark points.

  • 269.
    Devarakota, Pandu Ranga Rao
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Classification and Localization of Vehicle Occupants Using 3D Range Images2008Doctoral thesis, monograph (Other scientific)
    Abstract [en]

    This thesis deals with the problem of classifying automotive vehicle occupants and estimating their position. This information is critical in designing future smart airbag systems providing maximum protection for passengers. According to the American National Highway Traffic Safety Administration (NHTSA), since 1990, in the USA, 227 deaths have been attributed to airbags deployed in low-speed crashes which included 119 children, and 22 infants. In these cases, intelligent deployment of the airbag, based on the type and position of occupant could have avoided these fatalities. Current commercial classification systems based on traditional sensors, such as pressure sensors are not able to detect the position of occupants. Vision-based systems are advantageous over pressure sensor based systems, as they can provide additional functionalities like dynamic occupant position analysis or child seat orientation detection. On the other hand, vision-based systems have to cope with several challenges, such as, illumination conditions, temperature, humidity, large variation of scenes, cost, and computational aspects.

    This thesis presents new pattern recognition techniques for classifying, localizing and tracking vehicle occupants using a low-resolution 3-D optical time-of-flight range camera. This sensor is capable of providing directly a dense range image, independent of the illumination conditions and object textures. Based on this technology, IEE S.A. is presently developing a camera system for the application of occupant classification. A prototype of this camera has been the basis for this study. The first part of the thesis presents the problem of occupant classification. Herein, we investigate geometric feature extraction methods to discriminate between different occupant types. We develop features that are invariant under rotation and translation. A method for reducing the size of the feature set is analyzed with emphasis on robustness and low computational complexity while maintaining highly discriminative information. In addition, several classification methods are studied including Bayes quadratic classifier, Gaussian Mixture Model (GMM) classifier and polynomial classifier. We propose the use of a cluster based linear regression classifier using a polynomial kernel which is particularly well suited to coping with large variations within each class. Full scale experiments have been conducted which demonstrate that a classification reliability of almost 100\% can be achieved with the reduced feature set in combination with a cluster based classifier.

    In this safety critical application, it is equally important to address the problem of reliability estimation for the system. State-of-the-art methods to estimate the reliability of the classification are based either on classification output or based on density estimation. The second part of the thesis treats estimation of the reliability of the pattern classification system. Herein, a novel reliability measure is proposed for classification output which takes into account the local density of training data. Experiments verify that this reliability measure outperforms state-of-the-art methods in many cases.

    Lastly, the problem of dynamically detecting out-of-position occupants is addressed in the third part of the thesis. This task requires detecting and localizing the position of the occupant's head. Traditional head detection methods, such as detecting head-like objects in the image by analyzing the local shapes are not robust with the current sensor. Many regions in a scene such as the shoulder or the elbow of the occupant can be incorrectly detected as the head. In order to cope with these challenges, we exploit topology information in the range image. A modified Reeb graph technique has been developed that extracts a topological skeleton of the 3D contour that is invariant under rotation and translations. Results verify that the Reeb graph detects successfully the head i.e., the head always corresponds to one of the end points of the skeleton. Subsequently, a data association algorithm to select the correct head candidate out of the Reeb graph candidates is presented. Results show that the resulting head detection algorithm based on Reeb graphs is robust under scene changes.

  • 270.
    Devarakota, Pandu Ranga Rao
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Castillo-Franco, Marta
    IEE S. A., Luxembourg.
    Ginhoux, Romuald
    IEE S. A., Luxembourg.
    Mirbach, Bruno
    IEE S. A., Luxembourg.
    Kater, Serge
    IEE S. A., Luxembourg.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    3-D-Skeleton-Based Head Detection and Tracking Using Range Images2009In: IEEE Transactions on Vehicular Technology, ISSN 0018-9545, E-ISSN 1939-9359, Vol. 58, no 8, p. 4064-4077Article in journal (Refereed)
    Abstract [en]

    Vision-based 3-D head detection and tracking systems have been studied in several applications like video surveillance, face-detection systems, and occupant posture analysis. In this paper, we present the development of a topology-based framework using a 3-D skeletal model for the robust detection and tracking of a vehicle occupant's head position from low-resolution range image data for a passive safety system. Unlike previous approaches to head detection, the proposed approach explores the topology information of a scene to detect the position of the head. Among the different available topology representations, the Reeb graph technique is chosen and is adapted to low-resolution 3-D range images. Invariance of the graph under rotations is achieved by using a Morse radial distance function. To cope with the particular challenges such as the noise and the large variations in the density of the data, a voxel neighborhood connectivity notion is proposed. A multiple-hypothesis tracker (MHT) with nearest-neighbor data association and Kalman filter prediction is applied on the endpoints of the Reeb graph to select and filter the correct head candidate out of Reeb graph endpoints. A systematic evaluation of the head detection framework is carried out on full-scale experimental 3-D range images and compared with the ground truth. It is shown that the Reeb graph topology algorithm developed herein allows the correct detection of the head of the occupant with only two head candidates as input to the MHT. Results of the experiments demonstrate that the proposed framework is robust under the large variations of the scene. The processing requirements of the proposed approach are discussed. It is shown that the number of operations is rather low and that real-time processing requirements can be met with the proposed method.

  • 271.
    Devarakota, Pandu Ranga Rao
    et al.
    IEE S. A., Zone Industrielle, 2b Route de Tr`eves L-2632 Findel, Luxembourg..
    Mirbach, Bruno
    IEE S. A., Zone Industrielle, 2b Route de Tr`eves L-2632 Findel, Luxembourg..
    Castillo-Franco, Marta
    IEE S. A., Zone Industrielle, 2b Route de Tr`eves L-2632 Findel, Luxembourg..
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    3-D vision technology for occupant detection and classification2005In: Fifth International Conference on 3-D Digital Imaging and Modeling, Proceedings, LOS ALAMITOS: IEEE COMPUTER SOC , 2005, p. 72-79Conference paper (Refereed)
    Abstract [en]

    This paper describes a 3-D vision system based on a new 3-D sensor technology for the detection and classification of occupants in a car New generation of so-called "smart airbags" require the information about the occupancy type and position of the occupant. This information allows a distinct control of the airbag inflation. In order to reduce the risk of injuries due to airbag deployment, the airbag can be suppressed completely in case of a child seat oriented in reward direction. In this paper we propose a 3-D vision system based on a 3-D optical time-of-flight (TOF) sensor for the detection and classification of the occupancy on the passenger seat. Geometrical shape features are extracted from the 3-D image sequences. Polynomial classifier is considered for the classification task. A comparison of classifier performance with principle components (eigen-images) is presented. This paper also discuss the robustness of the features with variation of the data. The full scale tests have been conducted on a wide range of realistic situations (adults/children/child seats etc.) which may occur in a vehicle.

  • 272.
    Devarakota, Pandu Ranga Rao
    et al.
    IEE S.A., Zone Industrielle, 2b, Route de Tr`eves L-2632 Findel, Luxembourg.
    Mirbach, Bruno
    IEE S.A., Zone Industrielle, 2b, Route de Tr`eves L-2632 Findel, Luxembourg.
    Castillo-Franco, Marta
    IEE S.A., Zone Industrielle, 2b, Route de Tr`eves L-2632 Findel, Luxembourg.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Classification of vehicle occupants using 3D image sequences2005In: 2005 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH, AND SIGNAL PROCESSING, IEEE , 2005, p. 717-720Conference paper (Refereed)
    Abstract [en]

    The deployment of vehicle airbags for maximum protection requires information about the occupant's position, movement, weight, size etc. Specifically it is desirable to discriminate between adults, children, front- or rear faced child seats, objects put on the seat or simply empty seats. 2D images lack depth information about the object and are very sensitive to illumination conditions. Herein, occupant position classification techniques are developed based on low resolution 3D image sequences. The proposed methods are of low complexity and high reliability allowing real time implementation and meeting the rigorous requirements for passenger safety systems. Features are extracted from the 3D image sequences and a Sequential Forward Search (SFS) feature subset selection algorithm is employed to reduce the size of the feature set. Two classification techniques are evaluated, the B ayes quadratic classifier and the polynomial classifier. We present the classification results based on a large set of measurements from the low resolution 3D image sequences. The full scale tests have been conducted on a wide rance of realistic situations (adults/children/child seats etc.) which may occur in a vehicle.

  • 273.
    Devarakota, Pandu Ranga Rao
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Mirbach, Bruno
    IEE S.A., ZAE Weiergewan, 5326 Contern, Luxembourg.
    Ottersten, Björn
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Reliability estimation of a statistical classifier2008In: Pattern Recognition Letters, ISSN 0167-8655, E-ISSN 1872-7344, Vol. 29, no 3, p. 243-253Article in journal (Refereed)
    Abstract [en]

    Statistical pattern classification techniques have been successfully applied to many practical classification problems. In real-world applications, the challenge is often to cope with patterns that lead to unreliable classification decisions. These situations occur either due to unexpected patterns, i.e., patterns which occur in the regions far from the training data or due to patterns which occur in the overlap region of classes. This paper proposes a method for estimating the reliability of a classifier to cope with these situations. While existing methods for quantifying the reliability are often solely based on the class membership probability estimated on global approximations, in this paper, the reliability is quantified in terms of a confidence interval on the class membership probability. The size of the confidence interval is calculated explicitly based on the local density of training data in the neighborhood of a test pattern. A synthetic example is given to illustrate the various aspects of the proposed approach. In addition, experimental evaluation on real data sets is conducted to demonstrate the effectiveness of the proposed approach to detect unexpected patterns. The lower bound of the confidence interval is used to detect the unexpected patterns. By comparing the performance with the state-of-the-art methods, we show our approach is well-founded.

  • 274. Di Benedetto, M. D.
    et al.
    Innocenzo, A. D.
    Fischione, Carlo
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Isaksson, A. J.
    Johansson, Karl Henrik
    KTH, School of Electrical Engineering (EES), Automatic Control.
    Niculescu, S. -I
    Olaru, S.
    Sandou, G.
    Santucci, F.
    Serra, E.
    Tennina, S.
    Tiberi, U.
    Witrant, E.
    Wireless ventilation control for large-scale systems: The mining industrial case2009In: 2009 6th IEEE Annual Communications Society Conference on Sensor, Mesh and Ad Hoc Communications and Networks Workshops, 2009, Vol. SECON Workshops 2009Conference paper (Refereed)
    Abstract [en]

    Mining ventilation is an interesting example of a large scale system with high environmental impact where advanced control strategies can bring major improvements. Indeed, one of the first objectives of modern mining industry is to fulfill environmental specifications [1] during the ore extraction and crushing, by optimizing the energy consumption or the production of polluting agents. The mine electric consumption was 4 % of total industrial electric demand in the US in 1994 (6 % in 2007 in South Africa) and 90 % of it was related to motor system energy [2]. Another interesting figure is given in [3] where it is estimated that the savings associated with global control strategies for fluid systems (pumps, fans and compressors) represent approximately 20 % of the total manufacturing motor system energy savings. This motivates the development of new control strategies for large scale aerodynamic processes based on appropriate automation and a global consideration of the system. More specifically, the challenge in this work is focused on the mining ventilation since as much as 50 % or more of the energy consumed by the mining process may go into the ventilation (including heating the air). It is clear that investigating automatic control solutions and minimizing the amount of pumped air to save energy consumption (proportional to the cube of airflow quantity [4]) is of great environmental and industrial interest.

  • 275.
    Dixit, Abhishek
    et al.
    Ghent Univ iMinds, Dept Informat Technol, Ghent, Belgium..
    Mahloo, Mozhgan
    KTH, School of Information and Communication Technology (ICT), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
    Lannoo, Bart
    Ghent Univ iMinds, Dept Informat Technol, Ghent, Belgium..
    Chen, Jiajia
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
    Wosinska, Lena
    KTH, School of Electrical Engineering and Computer Science (EECS), Communication Systems, CoS, Optical Network Laboratory (ON Lab).
    Colle, Didier
    Ghent Univ iMinds, Dept Informat Technol, Ghent, Belgium..
    Pickavet, Mario
    Ghent Univ iMinds, Dept Informat Technol, Ghent, Belgium..
    Protection strategies for Next Generation Passive Optical Networks-22014In: 2014 INTERNATIONAL CONFERENCE ON OPTICAL NETWORK DESIGN AND MODELING, IEEE , 2014, p. 13-18Conference paper (Refereed)
    Abstract [en]

    Next Generation Passive Optical Networks-2 (NGPON2) are being considered to upgrade the current PON technology to meet the ever increasing bandwidth requirements of the end users while optimizing the network operators' investment. Reliability performance of NG-PON2 is very important due to the extended reach and, consequently, large number of served customers per PON segment. On the other hand, the use of more complex and hence more failure prone components than in the current PON systems may degrade reliability performance of the network. Thus designing reliable NG-PON2 architectures is of a paramount importance. Moreover, for appropriately evaluating network reliability performance, new models are required. For example, the commonly used reliability parameter, i.e., connection availability, defined as the percentage of time for which a connection remains operable, doesn't reflect the network wide reliability performance. The network operators are often more concerned about a single failure affecting a large number of customers than many uncorrelated failures disconnecting fewer customers while leading to the same average failure time. With this view, we introduce a new parameter for reliability performance evaluation, referred to as the failure impact. In this paper, we propose several reliable architectures for two important NGPON2 candidates: wavelength division multiplexed (WDM) PON and time and wavelength division multiplexed (TWDM) PON. Furthermore, we evaluate protection coverage, availability, failure impact and cost of the proposed schemes in order to identify the most efficient protection architecture.

  • 276. Dokhanchi, S. H.
    et al.
    Mysore, B. S.
    Mishra, K. V.
    Ottersten, Björn
    A mmWave Automotive Joint Radar-Communications System2019In: IEEE Transactions on Aerospace and Electronic Systems, ISSN 0018-9251, E-ISSN 1557-9603, Vol. 55, no 3, p. 1241-1260Article in journal (Refereed)
  • 277. Domouchtsidis, S.
    et al.
    Tsinos, C. G.
    Chatzinotas, S.
    Ottersten, Björn
    Symbol-Level Precoding for Low Complexity Transmitter Architectures in Large-Scale Antenna Array Systems2019In: IEEE Transactions on Wireless Communications, ISSN 1536-1276, E-ISSN 1558-2248, Vol. 18, no 2, p. 852-863Article in journal (Refereed)
  • 278.
    Drakakis, Konstantinos
    et al.
    University College Dublin.
    Rickard, Scott
    University College Dublin.
    de Fréin, Ruairí
    University College Dublin.
    Cichocki, Andrzej
    Laboratory for Advanced Brain Signal Processing Brain Science Institute RIKEN.
    Analysis of financial data using non-negative matrix factorisation2008In: International Mathematical Forum, ISSN 1312-7594, E-ISSN 1314-7536, Vol. 3, no 38, p. 1853-70Article in journal (Refereed)
    Abstract [en]

    We apply Non-negative Matrix Factorization (NMF) to the prob- lem of identifying underlying trends in stock market data. NMF is a recent and very successful tool for data analysis including image and audio processing; we use it here to decompose a mixture a data, the daily closing prices of the 30 stocks which make up the Dow Jones In- dustrial Average, into its constitute parts, the underlying trends which govern the financial marketplace. We demonstrate how to impose ap- propriate sparsity and smoothness constraints on the components of the decomposition. Also, we describe how the method clusters stocks to- gether in performance-based groupings which can be used for portfolio diversification.

  • 279.
    Drimus, Alin
    et al.
    Mads Clausen Institute for Product Innovation, University of Southern Denmark.
    Kootstra, Gert
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Bilberg, A.
    Mads Clausen Institute for Product Innovation, University of Southern Denmark.
    Kragic, Danica
    KTH, School of Computer Science and Communication (CSC), Computer Vision and Active Perception, CVAP. KTH, School of Computer Science and Communication (CSC), Centres, Centre for Autonomous Systems, CAS.
    Classification of Rigid and Deformable Objects Using a Novel Tactile Sensor2011In: Proceedings of the 15th International Conference on Advanced Robotics (ICAR), IEEE , 2011, p. 427-434Conference paper (Refereed)
    Abstract [en]

    In this paper, we present a novel tactile-array sensor for use in robotic grippers based on flexible piezoresistive rubber. We start by describing the physical principles of piezoresistive materials, and continue by outlining how to build a flexible tactile-sensor array using conductive thread electrodes. A real-time acquisition system scans the data from the array which is then further processed. We validate the properties of the sensor in an application that classifies a number of household objects while performing a palpation procedure with a robotic gripper. Based on the haptic feedback, we classify various rigid and deformable objects. We represent the array of tactile information as a time series of features and use this as the input for a k-nearest neighbors classifier. Dynamic time warping is used to calculate the distances between different time series. The results from our novel tactile sensor are compared to results obtained from an experimental setup using a Weiss Robotics tactile sensor with similar characteristics. We conclude by exemplifying how the results of the classification can be used in different robotic applications.

  • 280.
    Du, Jinfeng
    et al.
    Research Lab of Electronics, Massachusetts Institute of Technology, Cambridge, United States.
    Adams, David C.
    Research Lab of Electronics, Massachusetts Institute of Technology, Cambridge, United States.
    Médard, Muriel
    Research Lab of Electronics, Massachusetts Institute of Technology, Cambridge, United States.
    Cross-layer design of network-coded transmission with a delay constraint2015In: Proceedings of IEEE International Workshop on Signal Processing Advances in Wireless Communications (SPAWC), 2015, IEEE , 2015, p. 156-160Conference paper (Refereed)
    Abstract [en]

    We investigate the cross-layer design of wireless networks where end-to-end data transmission is subject to delayconstraint and there is no end-to-end feedback. The transmission is coded by random linear network coding (RLNC) on packet level to recover from packet erasures and by forward error-correction coding (FEC) on bit level to combatchannel distortions. Based on the two-layer model developed by Adams et al. where the end-to-end coded transmission ischaracterized by a throughput-reliability function, we formulate the cross-layer design as a goodput optimizationproblem relax the integrality constraint. We show that for single-hop transmissions there exists a globally optimal operating point for the relaxed problem. For multiple-hop transmissions, the goodput function is component-wiseconcave with respect to the physical layer data rate over each individual link.

  • 281.
    Dubois, Juliette
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Speech, Music and Hearing, TMH. ENSTA ParisTech.
    Elovsson, Anders
    KTH, School of Electrical Engineering and Computer Science (EECS), Speech, Music and Hearing, TMH.
    Friberg, Anders
    KTH, School of Electrical Engineering and Computer Science (EECS), Speech, Music and Hearing, TMH.
    Predicting Perceived Dissonance of Piano Chords Using a Chord-Class Invariant CNN and Deep Layered Learning2019In: Proceedings of 16th Sound & Music Computing Conference (SMC), Malaga, Spain, 2019, p. 530-536Conference paper (Refereed)
    Abstract [en]

    This paper presents a convolutional neural network (CNN) able to predict the perceived dissonance of piano chords. Ratings of dissonance for short audio excerpts were com- bined from two different datasets and groups of listeners. The CNN uses two branches in a directed acyclic graph (DAG). The first branch receives input from a pitch esti- mation algorithm, restructured into a pitch chroma. The second branch analyses interactions between close partials, known to affect our perception of dissonance and rough- ness. The analysis is pitch invariant in both branches, fa- cilitated by convolution across log-frequency and octave- wide max-pooling. Ensemble learning was used to im- prove the accuracy of the predictions. The coefficient of determination (R2) between rating and predictions are close to 0.7 in a cross-validation test of the combined dataset. The system significantly outperforms recent computational models. An ablation study tested the impact of the pitch chroma and partial analysis branches separately, conclud- ing that the deep layered learning approach with a pitch chroma was driving the high performance.

  • 282. Dutoit, T.
    et al.
    Holzapfel, André
    KTH, School of Computer Science and Communication (CSC), Media Technology and Interaction Design, MID.
    Jottrand, M.
    Moinet, A.
    Perez, J.
    Stylianou, Y.
    Towards a voice conversion system based on frame selection2007In: Proceedings of the IEEE International Conference on Acoustics, Speech, and Signal Processing (ICASSP), IEEE Press, 2007, Vol. IV, p. 513-516Conference paper (Refereed)
    Abstract [en]

    The subject of this paper is the conversion of a given speaker's voice (the source speaker) into another identified voice (the target one). We assume we have at our disposal a large amount of speech samples from source and target voice with at least a part of them being parallel. The proposed system is built on a mapping function between source and target spectral envelopes followed by a frame selection algorithm to produce final spectral envelopes. Converted speech is produced by a basic LP analysis of the source and LP synthesis using the converted spectral envelopes. We compared three types of conversion: without mapping, with mapping and using the excitation of the source speaker and finally with mapping using the excitation of the target. Results show that the combination of mapping and frame selection provide the best results, and underline the interest to work on methods to convert the LP excitation.

  • 283.
    Dwivedi, Satyam
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    De Angelis, Alessio
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    A Wideband Interference Power Estimator using a 1-bit Quantizer2011In: 2011 IEEE 22nd International Symposium On Personal Indoor And Mobile Radio Communications (PIMRC), New York: IEEE , 2011, p. 515-519Conference paper (Refereed)
    Abstract [en]

    This paper proposes a power estimation methodology which presents low complexity when implemented in hardware. Power estimation is done in digital and the radio signals are digitized using a 1-bit quantizer. An algorithm to estimate power is proposed. Power estimation of the signal is done while varying the threshold of the 1-bit quantizer. It is also shown that the proposed architecture can be used to estimate power of wideband radio channels.

  • 284.
    Dwivedi, Satyam
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    De Angelis, Alessio
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Scheduled UWB pulse transmissions for cooperative localization2012In: Ultra-Wideband (ICUWB), 2012 IEEE International Conference on, IEEE , 2012, p. 6-10Conference paper (Refereed)
    Abstract [en]

    In this paper we have proposed a technique for cooperative localization where localization is done in distributive fashion without using any additional broadcast by nodes. The method relies on a fixed scheduled ultra-wideband (UWB) pulse transmissions by nodes in a predetermined way. The advantages of the proposed method is simpler hardware, comparatively less pulse transmission in the system hence energy efficient and faster update rate.

  • 285.
    Dwivedi, Satyam
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    De Angelis, Alessio
    Zachariah, Dave
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Joint Ranging and Clock Parameter Estimation by Wireless Round Trip Time Measurements2015In: IEEE Journal on Selected Areas in Communications, ISSN 0733-8716, E-ISSN 1558-0008, Vol. 33, no 11, p. 2379-2390Article in journal (Refereed)
    Abstract [en]

    In this paper, we develop a new technique for estimating fine clock errors and range between two nodes simultaneously by two-way time-of-arrival measurements using impulse-radio ultrawideband signals. Estimators for clock parameters and the range are proposed, which are robust with respect to outliers. They are analyzed numerically and by means of experimental measurement campaigns. The technique and derived estimators achieve accuracies below 1 Hz for frequency estimation, below 1 ns for phase estimation, and 20 cm for range estimation, at a 4-m distance using 100-MHz clocks at both nodes. Therefore, we show that the proposed joint approach is practical and can simultaneously provide clock synchronization and positioning in an experimental system.

  • 286.
    Dwivedi, Satyam
    et al.
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Händel, Peter
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Precise Clock Parameter Estimation and Ground Truth Capture for Clock Error Measurements using FPGAs2014In: 2014 IEEE International Symposium on Precision Clock Synchronization for Measurement, Control and Communication (ISPCS), IEEE , 2014, p. 83-86Conference paper (Refereed)
    Abstract [en]

    In this extended abstract we discuss and propose a mechanism to estimate clock parameters between two clocks using TDC. Simultaneously, we have proposed a ground truth capture methodology for clock error measurements. In particular, we have proposed an accurate way of measuring clock phase ground truth at any instant in time using delay lines in FPGA. Accuracy of clock phase ground truth measurement can be up to 16 ps. We have estimated clock parameters from measurements and have compared it with clock ground truth obtained using suggested methods. Relative frequency errors are estimated with RMSE of 0.46 Hz and phase error is estimated with RMSE of 0.29 ns.

  • 287.
    Efraimsson, Nils
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Onset detection in polyphonic music2017Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    In music analysis, the beginning of events in a music signal (i.e. sound onset detection) is important for such tasks as sound segmentation, beat recognition and automatic music transcription. The aim of the present work was to make an algorithm for sound onset detection with better performance than other state-of-the-art1 algorithms. Necessary theoretical background for spectral analysis on a sound signal is given with special focus on the Short-Time Fourier Transform (STFT) and the effects of applying a window to a signal. Previous works based on different approaches to sound onset detection were studied, and a possible improvement was observed for one such approach - namely the one developed by Bello, Duxbury, Davies, & Sandler (2004). The algorithm uses an STFT approach, analyzing a sound signal time frame by time frame. The algorithm’s detection is sequential in nature: It takes a frame from the STFT and makes an extrapolation to the next frame, assuming that the signal is constant. The difference between the extrapolated frame and the actual frame of the STFT constitutes the detection function. The proposed improvement lies in a combination of ideas from other algorithms, analyzing the signal with different frequency bands with frequency dependent settings and a modification of the extrapolation step. The proposed algorithm is compared to the original algorithm and an adaption by Dixon (2006) by analyzing 20 songs using three different window functions. The results were evaluated with the standards set by MIREX (2005-2016). The results of the proposed algorithm are encouraging, showing good recall, but fail to out-perform any of the algorithms it is compared to in both precision and the so-called F-measure. The shortcomings of the proposed algorithm leave room for further improvement, and a number of possible future modifications are exemplified.

  • 288.
    Elowsson, Anders
    et al.
    KTH, School of Electrical Engineering and Computer Science (EECS), Speech, Music and Hearing, TMH.
    Friberg, Anders
    KTH, School of Electrical Engineering and Computer Science (EECS), Speech, Music and Hearing, TMH.
    Modeling Music Modality with a Key-Class Invariant Pitch Chroma CNN2019Conference paper (Refereed)
    Abstract [en]

    This paper presents a convolutional neural network (CNN) that uses input from a polyphonic pitch estimation system to predict perceived minor/major modality in music audio. The pitch activation input is structured to allow the first CNN layer to compute two pitch chromas focused on dif-ferent octaves. The following layers perform harmony analysis across chroma and time scales. Through max pooling across pitch, the CNN becomes invariant with re-gards to the key class (i.e., key disregarding mode) of the music. A multilayer perceptron combines the modality ac-tivation output with spectral features for the final predic-tion. The study uses a dataset of 203 excerpts rated by around 20 listeners each, a small challenging data size re-quiring a carefully designed parameter sharing. With an R2 of about 0.71, the system clearly outperforms previous sys-tems as well as individual human listeners. A final ablation study highlights the importance of using pitch activations processed across longer time scales, and using pooling to facilitate invariance with regards to the key class.

  • 289.
    Emilsson, Erika
    et al.
    Swedish Defence Research Agency (FOI),.
    Rydell, Joakim
    Swedish Defence Research Agency (FOI),.
    Rantakokko, Jouni
    KTH, School of Electrical Engineering (EES), Signal Processing.
    Multisensorsystem för positionering av rökdykare2013Conference paper (Other academic)
    Abstract [en]

    I det här arbetet presenteras en pågående studie riktad mot positionering och automatisk kartering för rökdykare. Fokus är på metoder för fusion av visuella och termiska kameror samt fotmonterad tröghetsnavigation.

  • 290.
    Eneman, Koen
    et al.
    Katholieke Univ Leuven.
    Leijon, Arne
    KTH, School of Electrical Engineering (EES), Sound and Image Processing.
    Doclo, Simon
    Univ. Oldenburg.
    Spriet, Ann
    Katholieke Univ Leuven.
    Moonen, Marc
    Kathlieke Univ Leuven.
    Wouters, Jan
    Katholieke Univ Leuven.
    Auditory-Profile-Based Physical Evaluation of Multi-Microphone Noise Reduction Techniques in Hearing Instruments2008In: Advances in Digital Speech Transmission / [ed] Rainer Martin, Ulrich Heute, Christiane Antweiler, John Wiley & Sons, 2008, p. 431-458Chapter in book (Other academic)
  • 291.
    Engström, Magnus
    et al.
    KTH, School of Technology and Health (STH), Medical Engineering, Computer and Electronic Engineering.
    Soheily, Nadia
    EKG-analys och presentation2014Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The interpretation of the ECG is an important method in the diagnosis of abnormal heart conditions and can be used proactively to discover previ-ously unknown heart problems. Being able to easily measure the ECG and get it analyzed and presented in a clear manner without having to consult a doctor is improtant to satisfy consumer needs.

    This report describes how an ECG signal is treated with different algo-rithms and methods to detect the heartbeat and its various parameters. This information is used to classify each heartbeat separately and thus determine whether the user has a normal or abnormal cardiac function. To achieve this a software prototype was developed in which the algorithms were implemented. A questionnaire survey was done in order to examine how the output of the software prototype should be presented for a user with no medical training.

    Seven ECG files from MIT-BIH Arrhythmia database were used for validation of the algorithms. The developed algorithms could detect of if any abnormality of heart function occurred and informed the users to consult a physician. The presentation of the heart function was based on the result from the questioner.

  • 292.
    Enqvist, Per
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Optimization and Systems Theory.
    On the simultaneous realization problem - Markov-parameter and covariance interpolation2006In: Signal Processing, ISSN 0165-1684, E-ISSN 1872-7557, Vol. 86, no 10, p. 3043-3054Article in journal (Refereed)
    Abstract [en]

    An efficient algorithm for determining the unique minimal and stable realization of a window of Markov parameters and covariances is derived. The main difference compared to the Q-Markov COVER theory is that here we let the variance of the input noise be a variable, thus avoiding a certain data consistency criterion. First, it is shown that maximizing the input variance of the realization over all interpolants yields a minimal degree solution-a result closely related to maximum entropy. Secondly, the state space approach of the Q-Markov COVER theory is used for analyzing the stability and structure of the realization by straightforward application of familiar realization theory concepts, in particular the occurrence of singular spectral measures is characterized.

  • 293.
    Eriksson, Jens
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Chord and modality analysis2016Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesis
    Abstract [en]

    The way humans listen to music and perceive its structure isautomatic. In an attempt by Friberg et al. (2011) to model thishuman perception mechanism, a set of nine perceptual features wasselected to describe the overall properties of music. By letting atest group rate the perceptual features in a data set of musicalpieces, they discovered that the factor with most importance fordescribing the emotions happy and sad was the perceptual featuremodality. Modality in music denotes whether the key of a musicalpiece is in major or minor.This thesis aims to predict the modality in a continuous scale (0-10) from chord analysis with multiple linear regression and a NeuralNetwork (NN) in a computational model using a custom set offeatures. The model was able to predict the modality with anexplained variability of 64 % using a NN. The results clearlyindicated that the approach of using chords as features to predictmodality, is appropriate for music data sets that consisted of tonalmusic.

  • 294.
    Esmaeilie, Ali
    KTH, School of Engineering Sciences in Chemistry, Biotechnology and Health (CBH), Biomedical Engineering and Health Systems, Health Informatics and Logistics.
    Utvärdering av statiska frekvensomformare till spårledningar för Stockholm tunnelbana2019Independent thesis Basic level (university diploma), 10 credits / 15 HE creditsStudent thesis
    Abstract [en]

    The subway is a very important means of transport in Stockholm and is in operation

    most of the day. The Red and Blue lines of the metro use an older signal system from

    the 60s. The system used for the signaling of the two lines is of the type AC power

    line with coding and uses relay switches.

    The track circuit that detects the position of different trains on the track use the frequency

    75 Hz. When converting the frequency 50 Hz to 75 Hz, carbon dust and heat

    losses is released to the space from the frequency converter. The carbon dust emitted

    into the air risks affecting relay functionality as it enters the relay housing and settles

    on the surface of the relay contacts in the space next to the frequency converter.

    The Traffic Administration have plans to upgrade the Red Line's signaling system in

    order to use the existing signaling system for another 25 years. The track circuit system

    positions and gives speed messages to the trains. A literature study has been

    conducted on the construction of the track circuit system and previous research has

    been conducted on frequency inverters to safely find a new frequency inverter that

    does not risk relay functionality. Through fact-finding from the Traffic Administration,

    new suitable frequency converters that could be replaced with the existing ones

    were investigated in this research.

    Static frequency converters were chosen to be investigated. According to the requirements

    of the Traffic Administration, four products were identified from different

    suppliers. None of the static frequency converters was directly compatible with existing

    systems because the system was built for a rotary frequency converter. "HZ-

    50-1105" from GoHz this model is available in 1-phase input and 1-phase output respectively.

    "FR-D 700" from Mitsubishi and "Micromaster 440" from Siemens which

    were equal in and out connection. "ACS-150" from ABB this model had a maximum

    rated power up to 4 kVA, which is only suitable for frequency inverters with a rated

    power of 2.5 kVA. The various types of static frequency inverters loaded the network

    in an asymmetrical way. Therefore, it was important to be able to distribute the load

    as evenly as possible on each phase. It was difficult to be able to rank the selected

    products without just showing the choices that existed when replacing rotary frequency

    converters. However, the use of static frequency inverters eliminates the

    risks of a rotating frequency converter. Static frequency converters can more accurately

    generate different frequencies and they have a shorter commissioning time;

    however, they load the network asymmetrically compared to rotating frequency converters.

  • 295.
    Fahlström Myrman, Arvid
    et al.
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH, Speech Communication and Technology.
    Salvi, Giampiero
    KTH, School of Computer Science and Communication (CSC), Speech, Music and Hearing, TMH.
    Partitioning of Posteriorgrams using Siamese Models for Unsupervised Acoustic Modelling2017In: Grounding Language Understanding, 2017Conference paper (Refereed)
  • 296. Fakoukakis, F. E.
    et al.
    Empliouk, Tz.
    Kolitsidas, Christos
    KTH, School of Electrical Engineering (EES), Electromagnetic Engineering.
    Ioannopoulos, G.
    Kyriacou, G. A.
    Ultra-Wideband butler matrix Fed MIMO antennas2015Conference paper (Refereed)
    Abstract [en]

    This work elaborates on the design of an Ultra-Wideband (UWB) Butler matrix fed antenna array, implementing a Multiple Input-Multiple Output (MIMO) configuration. The system aims at applications in future Long Term Evolution (LTE) and multifunctional Radar systems. Specifically, based on the results of our previous works, the research is extended towards the implementation of a MIMO beamforming scheme. Different beamforming scenarios are applied, in order to maximize system performance and minimize noise and interference. A comprehensive analysis and design procedure is presented, along with system simulation results.

  • 297.
    Falk, Johan
    KTH, Superseded Departments, Signals, Sensors and Systems.
    An electronic warfare perspective on time difference of arrival estimation subject to radio receiver imperfections2004Licentiate thesis, monograph (Other scientific)
    Abstract [en]

    In order to ensure secure communication in digital military radio systems, multiple methods are used to protect the transmission from being intercepted by enemy electronic warfare systems. An intercepted transmission can be used to estimate several parameters of the transmitted signal such as its origin (position or direction) and of course the transmitted message itself. The methods used in traditional electronic warfare direction-finding systems have in general poor performance against wideband low power signals while the considered correlation-based time-difference of arrival (TDOA) methods show promising results.

    The output from a TDOA-based direction-finding system using two spatially separated receivers is the TDOA for the signal between the receiving sensors which uniquely describes a hyperbolic curve and the emitter is located somewhere along this curve. In order to measure a TDOA between two digital radio receivers both receiver systems must have the same time and frequency references to avoid degradation due to reference imperfections. However, in some cases, the receivers are separated up to 1000 km and can not share a common reference. This is solved by using a reference module at each of the receiver sites and high accuracy is achieved using the NAVSTAR-GPS system but, still, small differences between the outputs of the different reference modules occurs which degrades the performance of the system.

    In a practical electronic warfare system there is a number of factors that degrade the performance of the system, such as non-ideal antennas, analog receiver filter differences, and the analog to digital converter errors. In this thesis we concentrate on the problems which arises from imperfections in the reference modules, such as time and frequency errors.

  • 298.
    Falk, Johan
    et al.
    Department of Electronic Warfare Systems, Swedish Defence Research Agency Linköping, Sweden.
    Händel, Peter
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Jansson, Magnus
    KTH, Superseded Departments, Signals, Sensors and Systems.
    Effects of frequency and phase error in electronic warfare TDOA direction-finding systems2003In: Military Communications Conference, IEEE conference proceedings, 2003, p. 118-123Conference paper (Refereed)
    Abstract [en]

    Electronic warfare systems for use against military communication sources include direction-finding. The considered direction-finding electronic-warfare system usestwo intercept receivers which is eavesdropping on thetransmitted signal with no knowledge of the waveformused, or its origin. Down-conversion to baseband is required in order to digitize the received signal. This canbe done using a superheterodyne receiver where an oscillator is used to mix the signal-of-interest to baseband.Errors in frequency and phase between the oscillatorsdegrade the performance. Because of this error, the per-formance derived in previous work by the authors willnot apply since the used model no longer is applicable.The extended model presented here considers the oscil-lator errors. The performance using the extended modelis determined numerically and the result is compared tothe Cramer-Rao lower bound for the ideal system usinga typical signal waveform.

  • 299.
    Farahini, Nasim
    et al.
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Li, Shuo
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Tajammul, Muhammad Adeel
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Shami, Muhammad Ali
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Chen, Guo
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Hemani, Ahmed
    KTH, School of Information and Communication Technology (ICT), Electronic Systems.
    Ye, Wei
    Huawei, Wireless Beijing Division, China.
    39.9 GOPs/watt multi-mode CGRA accelerator for a multi-standard basestation2013In: 2013 IEEE International Symposium on Circuits and Systems (ISCAS), IEEE , 2013, p. 1448-1451Conference paper (Refereed)
    Abstract [en]

    This paper presents an industrial case study of using a Coarse Grain Reconfigurable Architecture (CGRA) for a multi-mode accelerator for two kernels: FFT for the LTE standard and the Correlation Pool for the UMTS standard to be executed in a mutually exclusive manner. The CGRA multi-mode accelerator achieved computational efficiency of 39.94 GOPS/watt (OP is multiply-add) and silicon efficiency of 56.20 GOPS/mm2. By analyzing the code and inferring the unused features of the fully programmable solution, an in-house developed tool was used to automatically customize the design to run just the two kernels and the two efficiency metrics improved to 49.05 GOPS/watt and 107.57 GOPS/mm2. Corresponding numbers for the ASIC implementation are 63.84 GOPS/watt and 90.91 GOPS/mm2. Though the ASIC’s silicon and computational efficiency numbers are slightly better, the engineering efficiency of the pre-verified/characterized CGRA solution is at least 10X better than the ASIC solution.

  • 300.
    Farhadi, Hamed
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Coordinated Transmission for Wireless Interference Networks2014Doctoral thesis, monograph (Other academic)
    Abstract [en]

    Wireless interference networks refer to communication systems in which multiple source–destination pairs share the same transmission medium, and each source’s transmission interferes with the reception at non-intended destinations. Optimizing the transmission of each source–destination pair is interrelated with that of the other pairs, and characterizing the performance limits of these networks is a challenging task. Solving the problem of managing the interference and data communications for these networks would potentially make it possible to apply solutions to several existing and emerging communication systems. Wireless devices can carefully coordinate the use of scarce radio resources in order to deal effectively with interference and establish successful communications. In order to enable coordinated transmission, terminals must usually have a certain level of knowledge about the propagation environment; that is, channel state information (CSI). In practice, however, no CSI is a priori available at terminals (transmitters and receivers), and proper channel training mechanisms (such as pilot-based channel training and channel state feedback) should be employed to acquire CSI. This requires each terminal to share available radio resources between channel training and data transmissions. Allocating more resources for channel training leads to an accurate CSI estimation, and consequently, a precise coordination. However, it leaves fewer resources for data transmissions. This creates the need to investigate optimum resource allocation. This thesis investigates an information-theoretic approach towards the performance analysis of interference networks, and employs signal processing techniques to design transmission schemes for achieving these limits in the following scenarios. First, the smallest interference network with two single-input single-output (SISO) source–destination pairs is considered. A fixed-rate transmission is desired between each source–destination pair. Transmission schemes based on point-to-point codes are developed. The transmissions may not always attain successful communication, which means that outage events may be declared. The outage probability is quantified and the ε-outage achievable rate region is characterized. Next, a multi-user SISO interference network is studied. A pilot-assisted ergodic interference alignment (PAEIA) scheme is proposed to conduct channel training, channel state feedback, and data communications. The performance limits are evaluated, and optimum radio resource allocation problems are investigated. The analysis is extended to multi-cell wireless interference networks. A low-complexity pilot-assisted opportunistic user scheduling (PAOUS) scheme is proposed. The proposed scheme includes channel training, one-bit feedback transmission, user scheduling and data transmissions. The achievable rate region is computed, and the optimum number of cells that should be active simultaneously is determined. A multi-user MIMO interference network is also studied. Here, each source sends multiple data streams; specifically, the same number as the degrees of freedom of the network. Distributed transceiver design and power control algorithms are proposed that only require local CSI at terminals.

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