Rate Distortion Theory PDF Download

Author: Toby Berger
Publisher:
ISBN: 9780137531035
Category : Codage (Informatique)
Languages : en
Pages : 311

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Book Description

Author: Thomas M. Cover
Publisher: John Wiley & Sons
ISBN: 1118585771
Category : Computers
Languages : en
Pages : 788

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Book Description
The latest edition of this classic is updated with new problem sets and material The Second Edition of this fundamental textbook maintains the book's tradition of clear, thought-provoking instruction. Readers are provided once again with an instructive mix of mathematics, physics, statistics, and information theory. All the essential topics in information theory are covered in detail, including entropy, data compression, channel capacity, rate distortion, network information theory, and hypothesis testing. The authors provide readers with a solid understanding of the underlying theory and applications. Problem sets and a telegraphic summary at the end of each chapter further assist readers. The historical notes that follow each chapter recap the main points. The Second Edition features: * Chapters reorganized to improve teaching * 200 new problems * New material on source coding, portfolio theory, and feedback capacity * Updated references Now current and enhanced, the Second Edition of Elements of Information Theory remains the ideal textbook for upper-level undergraduate and graduate courses in electrical engineering, statistics, and telecommunications.

Author: Barry Michael Leiner
Publisher:
ISBN:
Category : Rate distortion theory
Languages : en
Pages : 206

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Book Description

Author: Jerry Gibson
Publisher: Morgan & Claypool Publishers
ISBN: 1598298089
Category : Technology & Engineering
Languages : en
Pages : 129

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Book Description
This book is very specifically targeted to problems in communications and compression by providing the fundamental principles and results in information theory and rate distortion theory for these applications and presenting methods that have proved and will prove useful in analyzing and designing real systems. The chapters contain treatments of entropy, mutual information, lossless source coding, channel capacity, and rate distortion theory; however, it is the selection, ordering, and presentation of the topics within these broad categories that is unique to this concise book. While the coverage of some standard topics is shortened or eliminated, the standard, but important, topics of the chain rules for entropy and mutual information, relative entropy, the data processing inequality, and the Markov chain condition receive a full treatment. Similarly, lossless source coding techniques presented include the Lempel-Ziv-Welch coding method. The material on rate Distortion theory and exploring fundamental limits on lossy source coding covers the often-neglected Shannon lower bound and the Shannon backward channel condition, rate distortion theory for sources with memory, and the extremely practical topic of rate distortion functions for composite sources. The target audience for the book consists of graduate students at the master's degree level and practicing engineers. It is hoped that practicing engineers can work through this book and comprehend the key results needed to understand the utility of information theory and rate distortion theory and then utilize the results presented to analyze and perhaps improve the communications and compression systems with which they are familiar.

Author: Guido M. Schuster
Publisher: Springer Science & Business Media
ISBN: 1475725663
Category : Computers
Languages : en
Pages : 305

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Book Description
One of the most intriguing problems in video processing is the removal of the redundancy or the compression of a video signal. There are a large number of applications which depend on video compression. Data compression represents the enabling technology behind the multimedia and digital television revolution. In motion compensated lossy video compression the original video sequence is first split into three new sources of information, segmentation, motion and residual error. These three information sources are then quantized, leading to a reduced rate for their representation but also to a distorted reconstructed video sequence. After the decomposition of the original source into segmentation, mo tion and residual error information is decided, the key remaining problem is the allocation of the available bits into these three sources of information. In this monograph a theory is developed which provides a solution to this fundamental bit allocation problem. It can be applied to all quad-tree-based motion com pensated video coders which use a first order differential pulse code modulation (DPCM) scheme for the encoding of the displacement vector field (DVF) and a block-based transform scheme for the encoding of the displaced frame differ ence (DFD). An optimal motion estimator which results in the smallest DFD energy for a given bit rate for the encoding of the DVF is also a result of this theory. Such a motion estimator is used to formulate a motion compensated interpolation scheme which incorporates a global smoothness constraint for the DVF.

Author: Imre Csiszár
Publisher: Elsevier
ISBN: 1483281574
Category : Mathematics
Languages : en
Pages : 465

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Book Description
Information Theory: Coding Theorems for Discrete Memoryless Systems presents mathematical models that involve independent random variables with finite range. This three-chapter text specifically describes the characteristic phenomena of information theory. Chapter 1 deals with information measures in simple coding problems, with emphasis on some formal properties of Shannon’s information and the non-block source coding. Chapter 2 describes the properties and practical aspects of the two-terminal systems. This chapter also examines the noisy channel coding problem, the computation of channel capacity, and the arbitrarily varying channels. Chapter 3 looks into the theory and practicality of multi-terminal systems. This book is intended primarily for graduate students and research workers in mathematics, electrical engineering, and computer science.

Author: Robert M. Gray
Publisher: Springer Science & Business Media
ISBN: 146131643X
Category : Technology & Engineering
Languages : en
Pages : 197

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Book Description
Source coding theory has as its goal the characterization of the optimal performance achievable in idealized communication systems which must code an information source for transmission over a digital communication or storage channel for transmission to a user. The user must decode the information into a form that is a good approximation to the original. A code is optimal within some class if it achieves the best possible fidelity given whatever constraints are imposed on the code by the available channel. In theory, the primary constraint imposed on a code by the channel is its rate or resolution, the number of bits per second or per input symbol that it can transmit from sender to receiver. In the real world, complexity may be as important as rate. The origins and the basic form of much of the theory date from Shan non's classical development of noiseless source coding and source coding subject to a fidelity criterion (also called rate-distortion theory) [73] [74]. Shannon combined a probabilistic notion of information with limit theo rems from ergodic theory and a random coding technique to describe the optimal performance of systems with a constrained rate but with uncon strained complexity and delay. An alternative approach called asymptotic or high rate quantization theory based on different techniques and approx imations was introduced by Bennett at approximately the same time [4]. This approach constrained the delay but allowed the rate to grow large.

Author: Jerry Gibson
Publisher: Springer Nature
ISBN: 3031016807
Category : Technology & Engineering
Languages : en
Pages : 115

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Book Description
This book is very specifically targeted to problems in communications and compression by providing the fundamental principles and results in information theory and rate distortion theory for these applications and presenting methods that have proved and will prove useful in analyzing and designing real systems. The chapters contain treatments of entropy, mutual information, lossless source coding, channel capacity, and rate distortion theory; however, it is the selection, ordering, and presentation of the topics within these broad categories that is unique to this concise book. While the coverage of some standard topics is shortened or eliminated, the standard, but important, topics of the chain rules for entropy and mutual information, relative entropy, the data processing inequality, and the Markov chain condition receive a full treatment. Similarly, lossless source coding techniques presented include the Lempel-Ziv-Welch coding method. The material on rate Distortion theory and exploring fundamental limits on lossy source coding covers the often-neglected Shannon lower bound and the Shannon backward channel condition, rate distortion theory for sources with memory, and the extremely practical topic of rate distortion functions for composite sources.

Author: Toby Berger
Publisher: Springer
ISBN: 3709129281
Category : Computers
Languages : en
Pages : 67

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Book Description

Author: Robert M. Gray
Publisher: Springer Science & Business Media
ISBN: 1475739826
Category : Computers
Languages : en
Pages : 346

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Book Description
This book is devoted to the theory of probabilistic information measures and their application to coding theorems for information sources and noisy channels. The eventual goal is a general development of Shannon's mathematical theory of communication, but much of the space is devoted to the tools and methods required to prove the Shannon coding theorems. These tools form an area common to ergodic theory and information theory and comprise several quantitative notions of the information in random variables, random processes, and dynamical systems. Examples are entropy, mutual information, conditional entropy, conditional information, and discrimination or relative entropy, along with the limiting normalized versions of these quantities such as entropy rate and information rate. Much of the book is concerned with their properties, especially the long term asymptotic behavior of sample information and expected information. This is the only up-to-date treatment of traditional information theory emphasizing ergodic theory.