Fundamentals of information theory and coding design. (©2002)
- Record Type:
- Book
- Title:
- Fundamentals of information theory and coding design. (©2002)
- Main Title:
- Fundamentals of information theory and coding design
- Further Information:
- Note: Roberto Togneri, Christopher J.S. deSilva.
- Other Names:
- Togneri, Roberto
DeSilva, Christopher J. S - Contents:
- ENTROPY AND INFORMATION; Structure; Structure in Randomness; First Concepts of Probability Theory; Surprise and Entropy; Units of Entropy; The Minimum and Maximum Values of Entropy; A Useful Inequality; Joint Probability Distribution Functions; Conditional Probability and Bayes' Theorem; Conditional Probability Distributions and Conditional Entropy; Information Sources; Memoryless Information Sources; Markov Sources and n-Gram Models; Stationary Distributions; The Entropy of Markov Sources; Sequences of Symbols; The Adjoint Source of a Markov Source; Extensions of Sources; Infinite Sample Spaces; INFORMATION CHANNELS; What Are Information Channels?; BSC and BEC Channels; Mutual Information; Noiseless and Deterministic Channels; Cascaded Channels; Additivity of Mutual Information; Channel Capacity: Maximum Mutual Information; Continuous Channels and Gaussian Channels; Information Capacity Theorem ; Rate Distortion Theory; SOURCE CODING; Introduction; Instantaneous Codes; The Kraft Inequality and McMillan's Theorem; Average Length and Compact Codes; Shannon's Noiseless Coding Theorem; Fano Coding; Huffman Coding; Arithmetic Coding; Higher-Order Modelling; DATA COMPRESSION; Introduction; Basic Concepts of Data Compression; Run-Length Coding; The CCITT Standard for Facsimile Transmission; Block-sorting Compression; Dictionary Coding; Statistical Compression; Prediction by Partial Matching; Image Coding; FUNDAMENTALS OF CHANNEL CODING; Introduction; Code Rate; Decoding Rules;ENTROPY AND INFORMATION; Structure; Structure in Randomness; First Concepts of Probability Theory; Surprise and Entropy; Units of Entropy; The Minimum and Maximum Values of Entropy; A Useful Inequality; Joint Probability Distribution Functions; Conditional Probability and Bayes' Theorem; Conditional Probability Distributions and Conditional Entropy; Information Sources; Memoryless Information Sources; Markov Sources and n-Gram Models; Stationary Distributions; The Entropy of Markov Sources; Sequences of Symbols; The Adjoint Source of a Markov Source; Extensions of Sources; Infinite Sample Spaces; INFORMATION CHANNELS; What Are Information Channels?; BSC and BEC Channels; Mutual Information; Noiseless and Deterministic Channels; Cascaded Channels; Additivity of Mutual Information; Channel Capacity: Maximum Mutual Information; Continuous Channels and Gaussian Channels; Information Capacity Theorem ; Rate Distortion Theory; SOURCE CODING; Introduction; Instantaneous Codes; The Kraft Inequality and McMillan's Theorem; Average Length and Compact Codes; Shannon's Noiseless Coding Theorem; Fano Coding; Huffman Coding; Arithmetic Coding; Higher-Order Modelling; DATA COMPRESSION; Introduction; Basic Concepts of Data Compression; Run-Length Coding; The CCITT Standard for Facsimile Transmission; Block-sorting Compression; Dictionary Coding; Statistical Compression; Prediction by Partial Matching; Image Coding; FUNDAMENTALS OF CHANNEL CODING; Introduction; Code Rate; Decoding Rules; Hamming Distance; Bounds on M, Maximal Codes and Perfect Codes; Error Probabilities; Shannon's Fundamental Coding Theorem; ERROR-CORRECTING CODES; Introduction; Groups; Rings and Fields; Linear Spaces; Linear Spaces over the Binary Field; Linear Codes; Encoding and Decoding; Codes Derived from Hadamard Matrices; CYCLIC CODES; Introduction; Rings of Polynomials; Cyclic Codes; Encoding and Decoding of Cyclic Codes; Encoding and Decoding Circuits for Cyclic Codes; The Golay Code; Hamming Codes; Cyclic Redundancy Check Codes; Reed-Muller Codes; BURST-CORRECTING CODES; Introduction; Finite Fields; Irreducible Polynomials; Construction of Finite Fields; Bursts of Errors; Fire Codes; Minimum Polynomials; Bose-Chaudhuri-Hocquenghem Codes; Other Fields; Reed-Solomon Codes; CONVOLUTIONAL CODES; Introduction; ASimple Example; Binary Convolutional Codes; Decoding Convolutional Codes; The Viterbi Algorithm; Sequential Decoding; Trellis Modulation; Turbo Codes; INDEX; ; Each chapter also contains a section of exercises and a section of references. … (more)
- Publisher Details:
- Boca Raton : Chapman & Hall/CRC
- Publication Date:
- 2002
- Copyright Date:
- 2002
- Extent:
- 1 online resource (xii, 385 pages), illustrations
- Subjects:
- 003/.54
Information theory
Coding theory
Teoría de la información
Coding theory
Information theory
Electronic books - Languages:
- English
- ISBNs:
- 0203998103
9780203998106 - Related ISBNs:
- 1584883103
- Notes:
- Note: Includes bibliographical references and index.
Note: Print version record. - Access Rights:
- Legal Deposit; Only available on premises controlled by the deposit library and to one user at any one time; The Legal Deposit Libraries (Non-Print Works) Regulations (UK).
- Access Usage:
- Restricted: Printing from this resource is governed by The Legal Deposit Libraries (Non-Print Works) Regulations (UK) and UK copyright law currently in force.
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- Available online (eLD content is only available in our Reading Rooms) ↗
- Physical Locations:
- British Library HMNTS - ELD.DS.155561
- Ingest File:
- 01_043.xml