Special Issue "Information Theory in Digital Signal Processing"

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

Deadline for manuscript submissions: 31 July 2021.

Special Issue Editors

Prof. Dr. Jorge Rocha
E-Mail Website
Guest Editor
Institute of Geography and Spatial Planning, University of Lisbon, 1600-276 Lisbon, Portugal
Interests: geosimulation; geocomputation; artificial neural networks; graphs theory; cellular automata; multi-agent systems; urban morphology; remote sensing; epidemiology; health geography; geomarketing; tourism; smart cities; big data
Special Issues and Collections in MDPI journals
Prof. Dr. José António Tenedório
E-Mail Website
Guest Editor
NOVA School of Social Sciences and Humanities, Interdisciplinary Centre of Social Sciences (CICS.NOVA), Universidade NOVA de Lisboa, Av. de Berna, 26-C, 1069-061 Lisboa, Portugal
Interests: Geography; GIScience; remote sensing; urban planning; urban data; sustainable cities
Special Issues and Collections in MDPI journals

Special Issue Information

Dear Colleagues,

Recent advances in signal processing and signal representation have brought to the forefront the need for a new understanding of the information content of signals and signal models. Progress, for instance, in sparsity and compressive has led to countless advances in signal processing.  However, a deficit in understanding both the information content of the innovative signal processing algorithms and the relations among information content and signal acquirement complexity still exists.

At the same time, the latest developments in information theory (IT) have proven its usage in a broader variety of research areas, far from its common uses in communications. Likewise, IT outlooks have powered new methods of both clustering and dimensionality reduction. The algorithm methods predominant in error improvement have led to advanced sparse signal retrieval methods, encouraging the use of IT tools in other emerging fields.

Signal processing in IT framework is mainly related to procedures and algorithms to accomplish IT standards. In any case, information is practically always characterized as some type of signal, hence making any employment of IT procedures irremovable from signal processing. The novel challenges developing from the new big data era are changing fields like statistics, machine learning, and data mining as information processing methods. Moreover, there are several fields central to signal processing that are of growing importance in the IT community, like machine learning.

The aim of this Special Issue is to bring together the signal processing, machine learning, and information theory communities. Thus, we encourage researchers to submit their latest works in IT for digital signal processing. Potential subjects include but are not limited to the following:

  • Signal processing, e.g., interference alignment, interference cancellation, and other multiuser capability accomplishing methods; full-duplex communication; and information acquisition.
  • Statistics and machine learning, e.g., computational efficiency and high-dimensional statistical theory.

Prof. Dr. Jorge Rocha
Prof. Dr. José António Tenedório
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 1800 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.

Keywords

  • remote sensing
  • complex systems
  • data mining
  • statistics
  • cartography
  • land use
  • planning

Published Papers (3 papers)

Order results
Result details
Select all
Export citation of selected articles as:

Research

Jump to: Review

Article
On the Performance of Video Resolution, Motion and Dynamism in Transmission Using Near-Capacity Transceiver for Wireless Communication
Entropy 2021, 23(5), 562; https://0-doi-org.brum.beds.ac.uk/10.3390/e23050562 - 01 May 2021
Viewed by 441
Abstract
This article investigates the performance of various sophisticated channel coding and transmission schemes for achieving reliable transmission of a highly compressed video stream. Novel error protection schemes including Non-Convergent Coding (NCC) scheme, Non-Convergent Coding assisted with Differential Space Time Spreading (DSTS) and Sphere [...] Read more.
This article investigates the performance of various sophisticated channel coding and transmission schemes for achieving reliable transmission of a highly compressed video stream. Novel error protection schemes including Non-Convergent Coding (NCC) scheme, Non-Convergent Coding assisted with Differential Space Time Spreading (DSTS) and Sphere Packing (SP) modulation (NCDSTS-SP) scheme and Convergent Coding assisted with DSTS and SP modulation (CDSTS-SP) are analyzed using Bit Error Ratio (BER) and Peak Signal to Noise Ratio (PSNR) performance metrics. Furthermore, error reduction is achieved using sophisticated transceiver comprising SP modulation technique assisted by Differential Space Time Spreading. The performance of the iterative Soft Bit Source Decoding (SBSD) in combination with channel codes is analyzed using various error protection setups by allocating consistent overall bit-rate budget. Additionally, the iterative behavior of SBSD assisted RSC decoder is analyzed with the aid of Extrinsic Information Transfer (EXIT) Chart in order to analyze the achievable turbo cliff of the iterative decoding process. The subjective and objective video quality performance of the proposed error protection schemes is analyzed while employing H.264 advanced video coding and H.265 high efficient video coding standards, while utilizing diverse video sequences having different resolution, motion and dynamism. It was observed that in the presence of noisy channel the low resolution videos outperforms its high resolution counterparts. Furthermore, it was observed that the performance of video sequence with low motion contents and dynamism outperforms relative to video sequence with high motion contents and dynamism. More specifically, it is observed that while utilizing H.265 video coding standard, the Non-Convergent Coding assisted with DSTS and SP modulation scheme with enhanced transmission mechanism results in Eb/N0 gain of 20 dB with reference to the Non-Convergent Coding and transmission mechanism at the objective PSNR value of 42 dB. It is important to mention that both the schemes have employed identical code rate. Furthermore, the Convergent Coding assisted with DSTS and SP modulation mechanism achieved superior performance with reference to the equivalent rate Non-Convergent Coding assisted with DSTS and SP modulation counterpart mechanism, with a performance gain of 16 dB at the objective PSNR grade of 42 dB. Moreover, it is observed that the maximum achievable PSNR gain through H.265 video coding standard is 45 dB, with a PSNR gain of 3 dB with reference to the identical code rate H.264 coding scheme. Full article
(This article belongs to the Special Issue Information Theory in Digital Signal Processing)
Show Figures

Figure 1

Article
Transmitter Diversity Gain Technique Aided Irregular Channel Coding for Mobile Video Transmission
Entropy 2021, 23(2), 235; https://0-doi-org.brum.beds.ac.uk/10.3390/e23020235 - 18 Feb 2021
Cited by 1 | Viewed by 797
Abstract
The reliable transmission of multimedia information that is coded through highly compression efficient encoders is a challenging task. This article presents the iterative convergence performance of IrRegular Convolutional Codes (IRCCs) with the aid of the multidimensional Sphere Packing (SP) modulation assisted Differential Space [...] Read more.
The reliable transmission of multimedia information that is coded through highly compression efficient encoders is a challenging task. This article presents the iterative convergence performance of IrRegular Convolutional Codes (IRCCs) with the aid of the multidimensional Sphere Packing (SP) modulation assisted Differential Space Time Spreading Codes (IRCC-SP-DSTS) scheme for the transmission of H.264/Advanced Video Coding (AVC) compressed video coded stream. In this article, three different regular and irregular error protection schemes are presented. In the presented Regular Error Protection (REP) scheme, all of the partitions of the video sequence are regular error protected with a rate of 3/4 IRCC. In Irregular Error Protection scheme-1 (IREP-1) the H.264/AVC partitions are prioritized as A, B & C, respectively. Whereas, in Irregular Error Protection scheme-2 (IREP-2), the H.264/AVC partitions are prioritized as B, A, and C, respectively. The performance of the iterative paradigm of an inner IRCC and outer Rate-1 Precoder is analyzed by the EXtrinsic Information Transfer (EXIT) Chart and the Quality of Experience (QoE) performance of the proposed mechanism is evaluated using the Bit Error Rate (BER) metric and Peak Signal to Noise Ratio (PSNR)-based objective quality metric. More specifically, it is concluded that the proposed IREP-2 scheme exhibits a gain of 1 dB Eb/N0 with reference to the IREP-1 and Eb/N0 gain of 0.6 dB with reference to the REP scheme over the PSNR degradation of 1 dB. Full article
(This article belongs to the Special Issue Information Theory in Digital Signal Processing)
Show Figures

Figure 1

Review

Jump to: Research

Review
Application of Dynamic Fragmentation Methods in Multimedia Databases: A Review
Entropy 2020, 22(12), 1352; https://0-doi-org.brum.beds.ac.uk/10.3390/e22121352 - 30 Nov 2020
Viewed by 713
Abstract
Fragmentation is a design technique widely used in multimedia databases, because it produces substantial benefits in reducing response times, causing lower execution costs in each operation performed. Multimedia databases include data whose main characteristic is their large size, therefore, database administrators face a [...] Read more.
Fragmentation is a design technique widely used in multimedia databases, because it produces substantial benefits in reducing response times, causing lower execution costs in each operation performed. Multimedia databases include data whose main characteristic is their large size, therefore, database administrators face a challenge of great importance, since they must contemplate the different qualities of non-trivial data. These databases over time undergo changes in their access patterns. Different fragmentation techniques presented in related studies show adequate workflows, however, some do not contemplate changes in access patterns. This paper aims to provide an in-depth review of the literature related to dynamic fragmentation of multimedia databases, to identify the main challenges, technologies employed, types of fragmentation used, and characteristics of the cost model. This review provides valuable information for database administrators by showing essential characteristics to perform proper fragmentation and to improve the performance of fragmentation schemes. The reduction of costs in fragmentation methods is one of the most desired main properties. To fulfill this objective, the works include cost models, covering different qualities. In this analysis, a set of characteristics used in the cost models of each work is presented to facilitate the creation of a new cost model including the most used qualities. In addition, different data sets or reference points used in the testing stage of each work analyzed are presented. Full article
(This article belongs to the Special Issue Information Theory in Digital Signal Processing)
Show Figures

Figure 1

Back to TopTop