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Publications (10 of 35) Show all publications
Elvander, F., Haasler, I., Jakobsson, A. & Karlsson, J. (2019). NON-COHERENT SENSOR FUSION VIA ENTROPY REGULARIZED OPTIMAL MASS TRANSPORT. In: 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP): . Paper presented at 44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), MAY 12-17, 2019, Brighton, ENGLAND (pp. 4415-4419). IEEE
Open this publication in new window or tab >>NON-COHERENT SENSOR FUSION VIA ENTROPY REGULARIZED OPTIMAL MASS TRANSPORT
2019 (English)In: 2019 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE , 2019, p. 4415-4419Conference paper, Published paper (Refereed)
Abstract [en]

This work presents a method for information fusion in source localization applications. The method utilizes the concept of optimal mass transport in order to construct estimates of the spatial spectrum using a convex barycenter formulation. We introduce an entropy regularization term to the convex objective, which allows for low-complexity iterations of the solution algorithm and thus makes the proposed method applicable also to higher-dimensional problems. We illustrate the proposed method's inherent robustness to misalignment and miscalibration of the sensor arrays using numerical examples of localization in two dimensions.

Place, publisher, year, edition, pages
IEEE, 2019
Series
International Conference on Acoustics Speech and Signal Processing ICASSP, ISSN 1520-6149
Keywords
Optimal mass transport, Entropy regularization, Target localization, Sensor fusion, Non-coherent processing
National Category
Other Mathematics
Identifiers
urn:nbn:se:kth:diva-261060 (URN)10.1109/ICASSP.2019.8682186 (DOI)000482554004130 ()2-s2.0-85069002151 (Scopus ID)978-1-4799-8131-1 (ISBN)
Conference
44th IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), MAY 12-17, 2019, Brighton, ENGLAND
Note

QC 20191002

Available from: 2019-10-02 Created: 2019-10-02 Last updated: 2019-10-02Bibliographically approved
Shariati, N., Zachariah, D., Karlsson, J. & Bengtsson, M. (2019). Robust Optimal Power Distribution for Hyperthermia Cancer Treatment. In: Hamed Farhadi (Ed.), Medical Internet of Things (m-IoT): (pp. 55-70). IntechOpen
Open this publication in new window or tab >>Robust Optimal Power Distribution for Hyperthermia Cancer Treatment
2019 (English)In: Medical Internet of Things (m-IoT) / [ed] Hamed Farhadi, IntechOpen , 2019, p. 55-70Chapter in book (Other academic)
Abstract [en]

We consider an optimization problem for spatial power distribution generated by an array of transmitting elements. Using ultrasound hyperthermia cancer treatment as a motivating example, the signal design problem consists of optimizing the power distribution across the tumor and healthy tissue regions, respectively. The models used in the optimization problem are, however, invariably subject to errors. To combat such unknown model errors, we formulate a robust signal design framework that can take the uncertainty into account using a worst-case approach. This leads to a semi-infinite programming (SIP) robust design problem, which we reformulate as a tractable convex problem that potentially has a wider range of applications.

Place, publisher, year, edition, pages
IntechOpen, 2019
National Category
Signal Processing
Identifiers
urn:nbn:se:kth:diva-259526 (URN)10.5772/intechopen.73281 (DOI)978-1-78985-092-5 (ISBN)978-1-78985-091-8 (ISBN)
Note

QC 20191015

Available from: 2019-09-17 Created: 2019-09-17 Last updated: 2019-10-15Bibliographically approved
Zhang, S., Ringh, A., Hu, X. & Karlsson, J. (2018). A moment-based approach to modeling collective behaviors. In: 2018 IEEE Conference on Decision and Control (CDC): . Paper presented at 57th IEEE Conference on Decision and Control, CDC 2018; Centre of the Fontainebleau in Miami Beach Miami; United States; 17 December 2018 through 19 December 2018 (pp. 1681-1687). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8619389.
Open this publication in new window or tab >>A moment-based approach to modeling collective behaviors
2018 (English)In: 2018 IEEE Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 1681-1687, article id 8619389Conference paper, Published paper (Refereed)
Abstract [en]

In this work we introduce an approach for modeling and analyzing collective behavior of a group of agents using moments. We represent the occupation measure of the group of agents by their moments and show how the dynamics of the moments can be modeled. Then approximate trajectories of the moments can be computed and an inverse problem is solved to recover macro-scale properties of the group of agents. To illustrate the theory, a numerical example with interactions between the agents is given.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Computer Vision and Robotics (Autonomous Systems)
Identifiers
urn:nbn:se:kth:diva-245104 (URN)10.1109/CDC.2018.8619389 (DOI)000458114801093 ()2-s2.0-85062188079 (Scopus ID)978-1-5386-1395-5 (ISBN)
Conference
57th IEEE Conference on Decision and Control, CDC 2018; Centre of the Fontainebleau in Miami Beach Miami; United States; 17 December 2018 through 19 December 2018
Note

QC 20190307

Available from: 2019-03-07 Created: 2019-03-07 Last updated: 2019-08-20Bibliographically approved
Elvander, F., Jakobsson, A. & Karlsson, J. (2018). Interpolation and Extrapolation of Toeplitz Matrices via Optimal Mass Transport. IEEE Transactions on Signal Processing, 66(20), 5285-5298
Open this publication in new window or tab >>Interpolation and Extrapolation of Toeplitz Matrices via Optimal Mass Transport
2018 (English)In: IEEE Transactions on Signal Processing, ISSN 1053-587X, E-ISSN 1941-0476, Vol. 66, no 20, p. 5285-5298Article in journal (Refereed) Published
Abstract [en]

In this work, we propose a novel method for quantifying distances between Toeplitz structured covariance matrices. By exploiting the spectral representation of Toeplitz matrices, the proposed distance measure is defined based on an optimal mass transport problem in the spectral domain. This may then be interpreted in the covariance domain, suggesting a natural way of interpolating and extrapolating Toeplitz matrices, such that the positive semidefiniteness and the Toeplitz structure of these matrices are preserved. The proposed distance measure is also shown to be contractive with respect to both additive and multiplicative noise and thereby allows for a quantification of the decreased distance between signals when these are corrupted by noise. Finally, we illustrate how this approach can be used for several applications in signal processing. In particular, we consider interpolation and extrapolation of Toeplitz matrices, as well as clustering problems and tracking of slowly varying stochastic processes.

Place, publisher, year, edition, pages
IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC, 2018
Keywords
Covariance interpolation, optimal mass transport, Toeplitz matrices, spectral estimation
National Category
Mathematics
Identifiers
urn:nbn:se:kth:diva-235558 (URN)10.1109/TSP.2018.2866432 (DOI)000444825200006 ()2-s2.0-85052704347 (Scopus ID)
Note

QC 20181002

Available from: 2018-10-02 Created: 2018-10-02 Last updated: 2018-10-02Bibliographically approved
Ringh, A., Karlsson, J. & Lindquist, A. (2018). Lower bounds on the maximum delay margin by analytic interpolation. In: 2018 IEEE 57th Annual Conference on Decision and Control (CDC): . Paper presented at IEEE 57th Annual Conference on Decision and Control (CDC),Miami Beach, FL, USA, December 17-19, 2018 (pp. 5463-5469). Institute of Electrical and Electronics Engineers (IEEE), Article ID 8618930.
Open this publication in new window or tab >>Lower bounds on the maximum delay margin by analytic interpolation
2018 (English)In: 2018 IEEE 57th Annual Conference on Decision and Control (CDC), Institute of Electrical and Electronics Engineers (IEEE), 2018, p. 5463-5469, article id 8618930Conference paper, Published paper (Refereed)
Abstract [en]

We study the delay margin problem in the context of recent works by T. Qi, J. Zhu, and J. Chen, where a sufficient condition for the maximal delay margin is formulated in terms of an interpolation problem obtained after introducing a rational approximation. Instead we omit the approximation step and solve the same problem directly using techniques from function theory and analytic interpolation. Furthermore, we introduce a constant shift in the domain of the interpolation problem. In this way we are able to improve on their lower bound for the maximum delay margin.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Control Engineering Other Mathematics
Identifiers
urn:nbn:se:kth:diva-239720 (URN)10.1109/CDC.2018.8618930 (DOI)000458114805008 ()2-s2.0-85062194089 (Scopus ID)9781538613955 (ISBN)
Conference
IEEE 57th Annual Conference on Decision and Control (CDC),Miami Beach, FL, USA, December 17-19, 2018
Funder
Swedish Research Council, 2014-5870
Note

QC 20181214

Available from: 2018-11-30 Created: 2018-11-30 Last updated: 2019-03-06Bibliographically approved
Chen, Y. & Karlsson, J. (2018). State Tracking of Linear Ensembles via Optimal Mass Transport. IEEE Control Systems Letters, 2(2), 260-265
Open this publication in new window or tab >>State Tracking of Linear Ensembles via Optimal Mass Transport
2018 (English)In: IEEE Control Systems Letters, ISSN 2475-1456, Vol. 2, no 2, p. 260-265Article in journal (Refereed) Published
Abstract [en]

We consider the problems of tracking an ensemble of indistinguishable agents with linear dynamics based only on output measurements. In this setting, the dynamics of the agents can be modeled by distribution flows in the state space and the measurements correspond to distributions in the output space. In this letter, we formulate the corresponding state estimation problem using optimal mass transport theory with prior linear dynamics, and the optimal solution gives an estimate of the state trajectories of the ensemble. For general distributions of systems this can be formulated as a convex optimization problem which is computationally feasible when the number of state dimensions is low. In the case where the marginal distributions are Gaussian, the problem is reformulated as a semidefinite programming problem and can be efficiently solved for tracking systems with a large number of states.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers Inc., 2018
Keywords
Agents-based systems, ensemble estimation, linear systems, nonlinear filtering, optimal mass transport, Convex optimization, Statistical mechanics, Convex optimization problems, Corresponding state, Estimation problem, Marginal distribution, Optimal solutions, Semidefinite programming problem, State trajectory, Dynamics
National Category
Computer and Information Sciences
Identifiers
urn:nbn:se:kth:diva-247222 (URN)10.1109/LCSYS.2018.2827001 (DOI)2-s2.0-85057647773 (Scopus ID)
Note

QC 20190403

Available from: 2019-04-03 Created: 2019-04-03 Last updated: 2019-04-03Bibliographically approved
Chen, Y., Karlsson, J. & Georgiou, T. T. (2018). The role of the time-arrow in mean-square estimation of stochastic processes. IEEE Control Systems Letters, 2(1), 85-90
Open this publication in new window or tab >>The role of the time-arrow in mean-square estimation of stochastic processes
2018 (English)In: IEEE Control Systems Letters, ISSN 2475-1456, Vol. 2, no 1, p. 85-90Article in journal (Refereed) Published
Abstract [en]

The purpose of this letter is to point out a certain dichotomy between the information that the past and future values of a multivariate stochastic process carry about the present. More specifically, vector-valued, secondorder stochastic processes may be deterministic in one time-direction but not in the other. This phenomenon, which is absent in scalar-valued processes, is deeply rooted in the geometry of the shift-operator. The exposition and the examples we discuss are based on the work of Douglas, Shapiro, and Shields on cyclic vectors of the backward shift and relate to classical ideas going back to Wiener and Kolmogorov. We focus on rank-one stochastic processes for which we obtain an explicit characterization of all regular processes that are deterministic in the reverse timedirection. This letter builds on examples and the goal is to provide insights to a control engineering audience with interests in estimation theory and modeling of time-series.

Place, publisher, year, edition, pages
Institute of Electrical and Electronics Engineers (IEEE), 2018
Keywords
Estimation, Linear stochastic systems
National Category
Mathematics
Identifiers
urn:nbn:se:kth:diva-246530 (URN)10.1109/LCSYS.2017.2740957 (DOI)2-s2.0-85057636580 (Scopus ID)
Note

QC 20190319

Available from: 2019-03-19 Created: 2019-03-19 Last updated: 2019-03-19Bibliographically approved
Elvander, F., Haasler, I., Jakobsson, A. & Karlsson, J. (2018). Tracking and sensor fusion in direction of arrival estimation using optimal mass transport. In: 2018 26th European Signal Processing Conference (EUSIPCO): . Paper presented at 26th European Signal Processing Conference, EUSIPCO 2018, Rome, Italy, 3 September 2018 through 7 September 2018 (pp. 1617-1621). European Signal Processing Conference, EUSIPCO
Open this publication in new window or tab >>Tracking and sensor fusion in direction of arrival estimation using optimal mass transport
2018 (English)In: 2018 26th European Signal Processing Conference (EUSIPCO), European Signal Processing Conference, EUSIPCO , 2018, p. 1617-1621Conference paper, Published paper (Refereed)
Abstract [en]

In this work, we propose new methods for information fusion and tracking in direction of arrival (DOA) estimation by utilizing an optimal mass transport framework. Sensor array measurements in DOA estimation may not be consistent due to misalignments and calibration errors. By using optimal mass transport as a notion of distance for combining the information obtained from all the sensor arrays, we obtain an approach that can prevent aliasing and is robust to array misalignments. For the case of sequential tracking, the proposed method updates the DOA estimate using the new measurements and an optimal mass transport prior. In the case of sensor fusion, information from several, individual, sensor arrays is combined using a barycenter formulation of optimal mass transport.

Place, publisher, year, edition, pages
European Signal Processing Conference, EUSIPCO, 2018
Series
European Signal Processing Conference, ISSN 2219-5491
Keywords
Direction of arrival, Optimal mass transport, Sensor fusion, Spectral estimation, Target tracking
National Category
Mathematics
Identifiers
urn:nbn:se:kth:diva-241524 (URN)10.23919/EUSIPCO.2018.8553068 (DOI)000455614900325 ()2-s2.0-85059812841 (Scopus ID)9789082797015 (ISBN)
Conference
26th European Signal Processing Conference, EUSIPCO 2018, Rome, Italy, 3 September 2018 through 7 September 2018
Funder
Swedish Research CouncilCarl Tryggers foundation
Note

QC 20190123

Available from: 2019-01-23 Created: 2019-01-23 Last updated: 2019-02-04Bibliographically approved
Elvander, F., Jakobsson, A. & Karlsson, J. (2018). USING OPTIMAL MASS TRANSPORT FOR TRACKING AND INTERPOLATION OF TOEPLITZ COVARIANCE MATRICES. In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP): . Paper presented at 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP) (pp. 4469-4473). IEEE
Open this publication in new window or tab >>USING OPTIMAL MASS TRANSPORT FOR TRACKING AND INTERPOLATION OF TOEPLITZ COVARIANCE MATRICES
2018 (English)In: 2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP), IEEE , 2018, p. 4469-4473Conference paper, Published paper (Refereed)
Abstract [en]

In this work, we propose a novel method for interpolation and extrapolation of Toeplitz structured covariance matrices. By considering a spectral representation of Toeplitz matrices, we use an optimal mass transport problem in the spectral domain in order to define a notion of distance between such matrices. The obtained optimal transport plan naturally induces a way of interpolating, as well as extrapolating, Toeplitz matrices. The constructed covariance matrix interpolants and extrapolants preserve the Toeplitz structure, as well as the positive semi-definiteness and the zeroth covariance of the original matrices. We demonstrate the proposed method's ability to model locally linear shifts of spectral power for slowly varying stochastic processes, illustrating the achievable performance using a simple tracking problem.

Place, publisher, year, edition, pages
IEEE, 2018
Keywords
Covariance interpolation, Optimal mass transport, Toeplitz matrices, Spectral estimation
National Category
Computational Mathematics
Identifiers
urn:nbn:se:kth:diva-237153 (URN)10.1109/ICASSP.2018.8462284 (DOI)000446384604127 ()2-s2.0-85054273067 (Scopus ID)
Conference
2018 IEEE INTERNATIONAL CONFERENCE ON ACOUSTICS, SPEECH AND SIGNAL PROCESSING (ICASSP)
Funder
Swedish Research Council
Note

QC 20181025

Available from: 2018-10-25 Created: 2018-10-25 Last updated: 2019-08-20Bibliographically approved
Ringh, A., Karlsson, J. & Lindquist, A. (2017). Further results on multidimensional rational covariance extension with application to texture generation. In: 2017 IEEE 56th Annual Conference on Decision and Control (CDC): . Paper presented at IEEE 56th Annual Conference on Decision and Control (CDC), DEC 12-15, 2017, Melbourne, AUSTRALIA. IEEE
Open this publication in new window or tab >>Further results on multidimensional rational covariance extension with application to texture generation
2017 (English)In: 2017 IEEE 56th Annual Conference on Decision and Control (CDC), IEEE , 2017Conference paper, Published paper (Refereed)
Abstract [en]

The rational covariance extension problem is a moment problem with several important applications in systems and control as, for example, in identification, estimation, and signal analysis. Here we consider the multidimensional counterpart and present new results for the well-posedness of the problem. We apply the theory to texture generation by modeling the texture as the output of a Wiener system. The static nonlinearity in the Wiener system is assumed to be a thresholding function and we identify both the linear dynamical system and the thresholding parameter.

Place, publisher, year, edition, pages
IEEE, 2017
Series
IEEE Conference on Decision and Control, ISSN 0743-1546
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Identifiers
urn:nbn:se:kth:diva-223868 (URN)10.1109/CDC.2017.8264252 (DOI)000424696903143 ()2-s2.0-85046261827 (Scopus ID)978-1-5090-2873-3 (ISBN)
Conference
IEEE 56th Annual Conference on Decision and Control (CDC), DEC 12-15, 2017, Melbourne, AUSTRALIA
Funder
Swedish Research CouncilSwedish Foundation for Strategic Research
Note

QC 20180306

Available from: 2018-03-06 Created: 2018-03-06 Last updated: 2018-12-04Bibliographically approved
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Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0001-5158-9255

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