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Book
Fundamentals in information theory and coding
Author:
ISBN: 3642448720 3642203469 3642203477 Year: 2011 Publisher: Berlin ; Heidelberg : Springer-Verlag,

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Abstract

The work introduces the fundamentals concerning the discrete information theory (measures of discrete information, mathematical modeling of discrete memoryless/memory sources and of discrete transmission channels) and the coding theory with its main components: compression, error control and encryption. The understanding of the theoretical matter is supported by many examples. One particular emphasis is put on the explanation of Genomic Coding. Many examples throughout the book are chosen from this particular area and several parts of the book are devoted to this exciting implication of coding. The book is interesting and highly valuable for educational purposes for students and all those who need basics in information theory and coding. Monica E. Borda is Professor in Information Theory and Coding, Cryptography and Genomic Signal Processing at the Technical University of Cluj-Napoca, Romania, having more than 30 years experience of education and research in the topics covered by the book. She has conducted research and Ph.D. thesis in coding theory, nonlinear signal and image processing, image watermarking, genomic signal processing, having authored and coauthored more than 100 research papers in national and international journals and conference proceedings. She is author and coauthor of 5 books in the mentioned fields.


Book
Randomness and elements of decision theory applied to signals
Author:
ISBN: 3030903141 3030903133 Year: 2021 Publisher: Cham, Switzerland : Springer,

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Digital
Fundamentals in Information Theory and Coding
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ISBN: 9783642203473 Year: 2011 Publisher: Berlin, Heidelberg Springer Berlin Heidelberg

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Book
Fundamentals in Information Theory and Coding
Authors: ---
ISBN: 9783642203473 Year: 2011 Publisher: Berlin, Heidelberg Springer Berlin Heidelberg

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Abstract

The work introduces the fundamentals concerning the discrete information theory (measures of discrete information, mathematical modeling of discrete memoryless/memory sources and of discrete transmission channels) and the coding theory with its main components: compression, error control and encryption. The understanding of the theoretical matter is supported by many examples. One particular emphasis is put on the explanation of Genomic Coding. Many examples throughout the book are chosen from this particular area and several parts of the book are devoted to this exciting implication of coding. The book is interesting and highly valuable for educational purposes for students and all those who need basics in information theory and coding. Monica E. Borda is Professor in Information Theory and Coding, Cryptography and Genomic Signal Processing at the Technical University of Cluj-Napoca, Romania, having more than 30 years experience of education and research in the topics covered by the book. She has conducted research and Ph.D. thesis in coding theory, nonlinear signal and image processing, image watermarking, genomic signal processing, having authored and coauthored more than 100 research papers in national and international journals and conference proceedings. She is author and coauthor of 5 books in the mentioned fields.


Book
Randomness and Elements of Decision Theory Applied to Signals
Authors: --- --- --- --- --- et al.
ISBN: 9783030903145 9783030903152 9783030903169 9783030903138 Year: 2021 Publisher: Cham Springer International Publishing :Imprint: Springer


Multi
Randomness and Elements of Decision Theory Applied to Signals
Authors: --- --- --- --- --- et al.
ISBN: 9783030903145 9783030903152 9783030903169 9783030903138 Year: 2021 Publisher: Cham Springer International Publishing :Imprint: Springer

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Abstract

This book offers an overview on the main modern important topics in random variables, random processes, and decision theory for solving real-world problems. After an introduction to concepts of statistics and signals, the book introduces many essential applications to signal processing like denoising, texture classification, histogram equalization, deep learning, or feature extraction. The book uses MATLAB algorithms to demonstrate the implementation of the theory to real systems. This makes the contents of the book relevant to students and professionals who need a quick introduction but practical introduction how to deal with random signals and processes.

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