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Information Theory And Coding By Example

Author: Mark Kelbert
Publisher: Cambridge University Press
ISBN: 0521769353
Size: 21.42 MB
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A valuable teaching aid. Provides relevant background material, many examples and clear solutions to problems taken from real exam papers.

Fundamentals In Information Theory And Coding

Author: Monica Borda
Publisher: Springer Science & Business Media
ISBN: 9783642203473
Size: 26.39 MB
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The work introduces the fundamentals concerning the measure of discrete information, the modeling of discrete sources without and with a memory, as well as of channels and coding. 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.

Introduction To Coding And Information Theory

Author: Steven Roman
Publisher: Springer Science & Business Media
ISBN: 9780387947044
Size: 22.91 MB
Format: PDF, Kindle
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This book is intended to introduce coding theory and information theory to undergraduate students of mathematics and computer science. It begins with a review of probablity theory as applied to finite sample spaces and a general introduction to the nature and types of codes. The two subsequent chapters discuss information theory: efficiency of codes, the entropy of information sources, and Shannon's Noiseless Coding Theorem. The remaining three chapters deal with coding theory: communication channels, decoding in the presence of errors, the general theory of linear codes, and such specific codes as Hamming codes, the simplex codes, and many others.

Information Theory And Coding Solved Problems

Author: Predrag Ivaniš
Publisher: Springer
ISBN: 3319493701
Size: 20.74 MB
Format: PDF, ePub, Docs
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This book is offers a comprehensive overview of information theory and error control coding, using a different approach then in existed literature. The chapters are organized according to the Shannon system model, where one block affects the others. A relatively brief theoretical introduction is provided at the beginning of every chapter, including a few additional examples and explanations, but without any proofs. And a short overview of some aspects of abstract algebra is given at the end of the corresponding chapters. The characteristic complex examples with a lot of illustrations and tables are chosen to provide detailed insights into the nature of the problem. Some limiting cases are presented to illustrate the connections with the theoretical bounds. The numerical values are carefully selected to provide in-depth explanations of the described algorithms. Although the examples in the different chapters can be considered separately, they are mutually connected and the conclusions for one considered problem relate to the others in the book.

Fundamentals Of Information Theory And Coding Design

Author: Roberto Togneri
Publisher: CRC Press
ISBN: 9780203998106
Size: 24.34 MB
Format: PDF
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Books on information theory and coding have proliferated over the last few years, but few succeed in covering the fundamentals without losing students in mathematical abstraction. Even fewer build the essential theoretical framework when presenting algorithms and implementation details of modern coding systems. Without abandoning the theoretical foundations, Fundamentals of Information Theory and Coding Design presents working algorithms and implementations that can be used to design and create real systems. The emphasis is on the underlying concepts governing information theory and the mathematical basis for modern coding systems, but the authors also provide the practical details of important codes like Reed-Solomon, BCH, and Turbo codes. Also setting this text apart are discussions on the cascading of information channels and the additivity of information, the details of arithmetic coding, and the connection between coding of extensions and Markov modelling. Complete, balanced coverage, an outstanding format, and a wealth of examples and exercises make this an outstanding text for upper-level students in computer science, mathematics, and engineering and a valuable reference for telecommunications engineers and coding theory researchers.

A First Course In Information Theory

Author: Raymond W. Yeung
Publisher: Springer Science & Business Media
ISBN: 1441986081
Size: 14.14 MB
Format: PDF, Kindle
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This book provides an up-to-date introduction to information theory. In addition to the classical topics discussed, it provides the first comprehensive treatment of the theory of I-Measure, network coding theory, Shannon and non-Shannon type information inequalities, and a relation between entropy and group theory. ITIP, a software package for proving information inequalities, is also included. With a large number of examples, illustrations, and original problems, this book is excellent as a textbook or reference book for a senior or graduate level course on the subject, as well as a reference for researchers in related fields.

A Student S Guide To Coding And Information Theory

Author: Stefan M. Moser
Publisher: Cambridge University Press
ISBN: 1107601967
Size: 65.99 MB
Format: PDF, Mobi
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A concise, easy-to-read guide, introducing beginners to the engineering background of modern communication systems, from mobile phones to data storage. Assuming only basic knowledge of high-school mathematics and including many practical examples and exercises to aid understanding, this is ideal for anyone who needs a quick introduction to the subject.

Information Theory

Author: Jan C. A. Lubbe (van der.)
Publisher: Cambridge University Press
ISBN: 9780521467605
Size: 77.34 MB
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Textbook on information theory, an important subject in electrical engineering and computer science.

Information Theory And Coding

Author: J.S.Chitode
Publisher: Technical Publications
ISBN: 9788184311914
Size: 28.23 MB
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Information Theory and Channel CapacityMeasure of Information, Average Information Content of Symbols in Long Independent Sequences, Average Information Content of Symbols in Long Dependent Sequences, Mark-off Statistical Model for Information Sources, Entropy and Information Rate of Mark-off Sources, Encoding of the Source Output, Shannon s Encoding Algorithm, Communication Channels, Discrete Communication Channels, Rate of Information Transmission Over a Discrete Channel, Capacity of a Discrete Memoryless Channel, Discrete Channels with Memory Continuous Channels, Shannon-Hartley Law and its Implications.Fundamental Limits on PerformanceSome Properties of Entropy, Extension of a DMS, Prefix Coding, Source Coding Theorem, Huffman Coding, Mutual Information, Properties of Mutual Information, Differential Entropy and Mutual Information for Continuous Ensembles.Error Control CodingRationale for Coding and Types of Codes, Discrete Memory less Channels, Examples of Error Control Coding, Methods of Controlling Errors, Types of Errors, Types of Codes, Linear Block Codes, Matrix Description of Linear Block Codes, Error Detection and Error Correction Capabilities of Linear Block Codes, Single Error Correcting Hamming Codes, Lookup Table (or Syndrome) Decoding using Standard Array, Binary Cyclic Codes, Algebraic Structures of Cyclic Codes, Encoding using and (n k) Bit Shift Register, Syndrome Calculation, Error Detection and Error Correction, BCH Codes, RS Codes, Golay Codes, Shortened Cyclic Codes, Burst Error Correcting Codes, Convolution Codes, Time Domain Approach, Transfer Domain Approach, State, Tree and Trellis diagrams, Encoders and Decoders (using Viterbi algorithm only) for (n,k,1) Convolution Codes.