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  • 1. Corander, Jukka
    et al.
    Gyllenberg, Mats
    Koski, Timo
    KTH, School of Engineering Sciences (SCI), Mathematics (Dept.), Mathematical Statistics.
    Learning Genetic Population Structures Using Minimization of Stochastic Complexity2010In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 12, no 5, p. 1102-1124Article in journal (Refereed)
    Abstract [en]

    Considerable research efforts have been devoted to probabilistic modeling of genetic population structures within the past decade. In particular, a wide spectrum of Bayesian models have been proposed for unlinked molecular marker data from diploid organisms. Here we derive a theoretical framework for learning genetic population structure of a haploid organism from bi-allelic markers for which potential patterns of dependence are a priori unknown and to be explicitly incorporated in the model. Our framework is based on the principle of minimizing stochastic complexity of an unsupervised classification under tree augmented factorization of the predictive data distribution. We discuss a fast implementation of the learning framework using deterministic algorithms.

  • 2. Do, Hieu T.
    et al.
    Oechtering, Tobias J.
    KTH, School of Electrical Engineering (EES).
    Skoglund, Mikael
    KTH, School of Electrical Engineering (EES).
    Vu, Mai
    Interfering Relay Channels2017In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 19, no 9, article id 441Article in journal (Refereed)
    Abstract [en]

    This paper introduces and studies a model in which two relay channels interfere with each other. Motivated by practical scenarios in heterogeneous wireless access networks, each relay is assumed to be connected to its intended receiver through a digital link with finite capacity. Inner and outer bounds for achievable rates are derived and shown to be tight for new discrete memoryless classes, which generalize and unify several known cases involving interference and relay channels. Capacity region and sum capacity for multiple Gaussian scenarios are also characterized to within a constant gap. The results show the optimality or near-optimality of the quantize-bin-and-forward coding scheme for practically relevant relay-interference networks, which brings important engineering insight into the design of wireless communications systems.

  • 3.
    Huang, Sheng
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory.
    Skoglund, Mikael
    KTH, School of Electrical Engineering (EES), Communication Theory.
    On linear coding over finite rings and applications to computing2017In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 19, no 5, article id 233Article in journal (Refereed)
    Abstract [en]

    This paper presents a coding theorem for linear coding over finite rings, in the setting of the Slepian-Wolf source coding problem. This theorem covers corresponding achievability theorems of Elias (IRE Conv. Rec. 1955, 3, 37-46) and Csiszár (IEEE Trans. Inf. Theory 1982, 28, 585-592) for linear coding over finite fields as special cases. In addition, it is shown that, for any set of finite correlated discrete memoryless sources, there always exists a sequence of linear encoders over some finite non-field rings which achieves the data compression limit, the Slepian-Wolf region. Hence, the optimality problem regarding linear coding over finite non-field rings for data compression is closed with positive confirmation with respect to existence. For application, we address the problem of source coding for computing, where the decoder is interested in recovering a discrete function of the data generated and independently encoded by several correlated i.i.d. random sources. We propose linear coding over finite rings as an alternative solution to this problem. Results in Körner-Marton (IEEE Trans. Inf. Theory 1979, 25, 219-221) and Ahlswede-Han (IEEE Trans. Inf. Theory 1983, 29, 396-411, Theorem 10) are generalized to cases for encoding (pseudo) nomographic functions (over rings). Since a discrete function with a finite domain always admits a nomographic presentation, we conclude that both generalizations universally apply for encoding all discrete functions of finite domains. Based on these, we demonstrate that linear coding over finite rings strictly outperforms its field counterpart in terms of achieving better coding rates and reducing the required alphabet sizes of the encoders for encoding infinitely many discrete functions.

  • 4.
    Lundqvist, Per
    et al.
    KTH, School of Industrial Engineering and Management (ITM), Energy Technology.
    Öhman, Henrik
    KTH, School of Industrial Engineering and Management (ITM), Energy Technology, Applied Thermodynamics and Refrigeration.
    Global Efficiency of Heat Engines and Heat Pumps with Non-Linear Boundary Conditions2017In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 19, no 8, article id 394Article in journal (Refereed)
    Abstract [en]

    Analysis of global energy efficiency of thermal systems is of practical importance for a number of reasons. Cycles and processes used in thermal systems exist in very different configurations, making comparison difficult if specific models are required to analyze specific thermal systems. Thermal systems with small temperature differences between a hot side and a cold side also suffer from difficulties due to heat transfer pinch point effects. Such pinch points are consequences of thermal systems design and must therefore be integrated in the global evaluation. In optimizing thermal systems, detailed entropy generation analysis is suitable to identify performance losses caused by cycle components. In plant analysis, a similar logic applies with the difference that the thermal system is then only a component, often industrially standardized. This article presents how a thermodynamic "black box" method for defining and comparing thermal efficiency of different size and types of heat engines can be extended to also compare heat pumps of different apparent magnitude and type. Impact of a non-linear boundary condition on reversible thermal efficiency is exemplified and a correlation of average real heat engine efficiencies is discussed in the light of linear and non-linear boundary conditions.

  • 5.
    Nasiri Khormuji, Majid
    et al.
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Skoglund, Mikael
    KTH, School of Electrical Engineering (EES), Communication Theory. KTH, School of Electrical Engineering (EES), Centres, ACCESS Linnaeus Centre.
    Capacity bounds and mapping design for binary symmetric relay channels2012In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 14, no 12, p. 2589-2610Article in journal (Refereed)
    Abstract [en]

    Capacity bounds for a three-node binary symmetric relay channel with orthogonal components at the destination are studied. The cut-set upper bound and the rates achievable using decode-and-forward (DF), partial DF and compress-and-forward (CF) relaying are first evaluated. Then relaying strategies with finite memory-length are considered. An efficient algorithm for optimizing the relay functions is presented.The Boolean Fourier transform is then employed to unveil the structure of the optimized mappings. Interestingly, the optimized relay functions exhibit a simple structure. Numerical results illustrate that the rates achieved using the optimized low-dimensional functions are either comparable to those achieved by CF orsuperior to those achieved by DF relaying.In particular, the optimized low-dimensional relaying scheme can improve on DF relaying when the quality of the source-relay link is worse than or comparable to that of other links.

  • 6. Sadat, E. S.
    et al.
    Faez, K.
    Pour, Mohsen Saffari
    KTH.
    Entropy-based video steganalysis of motion vectors2018In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300, Vol. 20, no 4, article id 244Article in journal (Refereed)
    Abstract [en]

    In this paper, a new method is proposed for motion vector steganalysis using the entropy value and its combination with the features of the optimized motion vector. In this method, the entropy of blocks is calculated to determine their texture and the precision of their motion vectors. Then, by using a fuzzy cluster, the blocks are clustered into the blocks with high and low texture, while the membership function of each block to a high texture class indicates the texture of that block. These membership functions are used to weight the effective features that are extracted by reconstructing the motion estimation equations. Characteristics of the results indicate that the use of entropy and the irregularity of each block increases the precision of the final video classification into cover and stego classes. 

  • 7. Sadat, Elaheh Sadat
    et al.
    Faez, Karim
    Saffari Pour, Mohsen
    KTH, School of Industrial Engineering and Management (ITM), Materials Science and Engineering, Energy and Furnace Technology. KTH, School of Industrial Engineering and Management (ITM), Materials Science and Engineering, Applied Process Metallurgy.
    Entropy-Based Video Steganalysis of Motion Vectors2018In: Entropy, ISSN 1099-4300, E-ISSN 1099-4300Article in journal (Refereed)
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