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Special Issue "Information Theory Applications in Signal Processing"

A special issue of Entropy (ISSN 1099-4300). This special issue belongs to the section "Information Theory".

Deadline for manuscript submissions: 30 November 2018

Special Issue Editors

Guest Editor
Dr. Sergio Cruces

Departamento de Teoría de la Señal y Comunicaciones, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092 Seville, Spain
Website | E-Mail
Interests: signal processing; information theory; machine learning; communications; audio
Guest Editor
Dr. Rubén Martín-Clemente

Departamento de Teoría de la Señal y Comunicaciones, Universidad de Sevilla, Camino de los Descubrimientos s/n, 41092 Seville, Spain
Website | E-Mail
Interests: digital signal processing; biomedical engineering; digital communications
Guest Editor
Dr. Wojciech Samek

Fraunhofer Heinrich Hertz Institute HHI, 10587 Berlin, Germany
Website | E-Mail
Interests: machine learning; interpretability; deep learning; artificial intelligence; robust signal processing

Special Issue Information

Dear Colleagues,

Information theory plays a fundamental role in the determination of theoretical performance limits for statistical estimation, detection, and compression. Its remarkable history of success during the last few decades has fueled research on information-guided principles for data analysis and signal processing. These dynamic and fast-growing fields have to cope with increasingly complex scenarios and novel applications in component analysis, machine learning, and communications. Hence, there is a need for specific information theoretic criteria and algorithms that work in each of the considered situations and attain a set of desired goals, for instance, an enhancement in the interpretability of the solutions, improvements in performance, robustness with respect to the model uncertainties and possible data perturbations, a reliable convergence for the algorithms and any other kind of theoretical guarantees.

In this Special Issue, we encourage researchers to present their original and recent developments in information theory for advanced methods in signal processing. Possible topics include, but are not limited to, the following:

  • Information criteria, divergence measures and algorithms for source separation, independent component analysis, matrix/tensor decompositions, data approximation and completion, low-rank and sparse based methods.
  • Applications in machine learning, including supervised and unsupervised methods, data representation, dimensionality reduction, feature extraction, Bayesian approaches and deep learning.
  • Applications in statistical signal processing, including parameter estimation, system identification, pattern classification, signal approximation and compressed sensing, signal analysis and restoration.
  • Applications in biomedical engineering, speech/audio processing, and communications.

Dr. Sergio Cruces
Dr. Rubén Martín-Clemente
Dr. Wojciech Samek
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All papers will be peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Entropy is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1500 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Published Papers (2 papers)

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Research

Open AccessArticle Dynamic Rounds Chaotic Block Cipher Based on Keyword Abstract Extraction
Entropy 2018, 20(9), 693; https://doi.org/10.3390/e20090693
Received: 5 July 2018 / Revised: 28 August 2018 / Accepted: 8 September 2018 / Published: 11 September 2018
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Abstract
According to the keyword abstract extraction function in the Natural Language Processing and Information Retrieval Sharing Platform (NLPIR), the design method of a dynamic rounds chaotic block cipher is presented in this paper, which takes into account both the security and efficiency. The
[...] Read more.
According to the keyword abstract extraction function in the Natural Language Processing and Information Retrieval Sharing Platform (NLPIR), the design method of a dynamic rounds chaotic block cipher is presented in this paper, which takes into account both the security and efficiency. The cipher combines chaotic theory with the Feistel structure block cipher, and uses the randomness of chaotic sequence and the nonlinearity of chaotic S-box to dynamically generate encrypted rounds, realizing more numbers of dynamic rounds encryption for the important information marked by NLPIR, while less numbers of dynamic rounds encryption for the non-important information that is not marked. Through linear and differential cryptographic analysis, ciphertext information entropy, “0–1” balance and National Institute of Science and Technology (NIST) tests and the comparison with other traditional and lightweight block ciphers, the results indicate that the dynamic variety of encrypted rounds can achieve different levels of encryption for different information, which can achieve the purpose of enhancing the anti-attack ability and reducing the number of encrypted rounds. Therefore, the dynamic rounds chaotic block cipher can guarantee the security of information transmission and realize the lightweight of the cryptographic algorithm. Full article
(This article belongs to the Special Issue Information Theory Applications in Signal Processing)
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Open AccessArticle Achievable Rate Region under Linear Beamforming for Dual-Hop Multiple-Access Relay Network
Entropy 2018, 20(8), 547; https://doi.org/10.3390/e20080547
Received: 20 May 2018 / Revised: 18 July 2018 / Accepted: 21 July 2018 / Published: 24 July 2018
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Abstract
Consider a network consisting of two independent single-antenna sources, a single-antenna destination and a helping multiple-antenna relay. This network is called a dual-hop multiple access relay network (MARN). In this network, sources transmit to the relay simultaneously in the first time slot. The
[...] Read more.
Consider a network consisting of two independent single-antenna sources, a single-antenna destination and a helping multiple-antenna relay. This network is called a dual-hop multiple access relay network (MARN). In this network, sources transmit to the relay simultaneously in the first time slot. The relay retransmits the received sum-signal to the destination using a linear beamforming scheme in the second time slot. In this paper, we characterize the achievable rate region of MARN under linear beamforming. The achievable rate region characterization problem is first transformed to an equivalent “corner point” optimization problem with respect to linear beamforming matrix at the relay. Then, we present an efficient algorithm to solve it via only semi-definite programming (SDP). We further derive the mathematical close-forms of the maximum individual rates and the sum-rate. Finally, numerical results demonstrate the performance of the proposed schemes. Full article
(This article belongs to the Special Issue Information Theory Applications in Signal Processing)
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