Error Correction Coding

Error Correction Coding

Author: Todd K. Moon

Publisher: John Wiley & Sons

Published: 2005-06-06

Total Pages: 800

ISBN-13: 0471648000

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An unparalleled learning tool and guide to error correction coding Error correction coding techniques allow the detection and correction of errors occurring during the transmission of data in digital communication systems. These techniques are nearly universally employed in modern communication systems, and are thus an important component of the modern information economy. Error Correction Coding: Mathematical Methods and Algorithms provides a comprehensive introduction to both the theoretical and practical aspects of error correction coding, with a presentation suitable for a wide variety of audiences, including graduate students in electrical engineering, mathematics, or computer science. The pedagogy is arranged so that the mathematical concepts are presented incrementally, followed immediately by applications to coding. A large number of exercises expand and deepen students' understanding. A unique feature of the book is a set of programming laboratories, supplemented with over 250 programs and functions on an associated Web site, which provides hands-on experience and a better understanding of the material. These laboratories lead students through the implementation and evaluation of Hamming codes, CRC codes, BCH and R-S codes, convolutional codes, turbo codes, and LDPC codes. This text offers both "classical" coding theory-such as Hamming, BCH, Reed-Solomon, Reed-Muller, and convolutional codes-as well as modern codes and decoding methods, including turbo codes, LDPC codes, repeat-accumulate codes, space time codes, factor graphs, soft-decision decoding, Guruswami-Sudan decoding, EXIT charts, and iterative decoding. Theoretical complements on performance and bounds are presented. Coding is also put into its communications and information theoretic context and connections are drawn to public key cryptosystems. Ideal as a classroom resource and a professional reference, this thorough guide will benefit electrical and computer engineers, mathematicians, students, researchers, and scientists.


Mathematical Foundations for Signal Processing, Communications, and Networking

Mathematical Foundations for Signal Processing, Communications, and Networking

Author: Erchin Serpedin

Publisher: CRC Press

Published: 2017-12-04

Total Pages: 852

ISBN-13: 1439855145

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Mathematical Foundations for Signal Processing, Communications, and Networking describes mathematical concepts and results important in the design, analysis, and optimization of signal processing algorithms, modern communication systems, and networks. Helping readers master key techniques and comprehend the current research literature, the book offers a comprehensive overview of methods and applications from linear algebra, numerical analysis, statistics, probability, stochastic processes, and optimization. From basic transforms to Monte Carlo simulation to linear programming, the text covers a broad range of mathematical techniques essential to understanding the concepts and results in signal processing, telecommunications, and networking. Along with discussing mathematical theory, each self-contained chapter presents examples that illustrate the use of various mathematical concepts to solve different applications. Each chapter also includes a set of homework exercises and readings for additional study. This text helps readers understand fundamental and advanced results as well as recent research trends in the interrelated fields of signal processing, telecommunications, and networking. It provides all the necessary mathematical background to prepare students for more advanced courses and train specialists working in these areas.


Fast Algorithms for Signal Processing

Fast Algorithms for Signal Processing

Author: Richard E. Blahut

Publisher: Cambridge University Press

Published: 2010-06-24

Total Pages: 469

ISBN-13: 1139487957

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Efficient signal processing algorithms are important for embedded and power-limited applications since, by reducing the number of computations, power consumption can be reduced significantly. Similarly, efficient algorithms are also critical to very large scale applications such as video processing and four-dimensional medical imaging. This self-contained guide, the only one of its kind, enables engineers to find the optimum fast algorithm for a specific application. It presents a broad range of computationally-efficient algorithms, describes their structure and implementation, and compares their relative strengths for given problems. All the necessary background mathematics is included and theorems are rigorously proved, so all the information needed to learn and apply the techniques is provided in one convenient guide. With this practical reference, researchers and practitioners in electrical engineering, applied mathematics, and computer science can reduce power dissipation for low-end applications of signal processing, and extend the reach of high-end applications.


Synthesis and Optimization of DSP Algorithms

Synthesis and Optimization of DSP Algorithms

Author: George Constantinides

Publisher: Springer Science & Business Media

Published: 2004-04-30

Total Pages: 170

ISBN-13: 1402079303

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Synthesis and Optimization of DSP Algorithms describes approaches taken to synthesising structural hardware descriptions of digital circuits from high-level descriptions of Digital Signal Processing (DSP) algorithms. The book contains: -A tutorial on the subjects of digital design and architectural synthesis, intended for DSP engineers, -A tutorial on the subject of DSP, intended for digital designers, -A discussion of techniques for estimating the peak values likely to occur in a DSP system, thus enabling an appropriate signal scaling. Analytic techniques, simulation techniques, and hybrids are discussed. The applicability of different analytic approaches to different types of DSP design is covered, -The development of techniques to optimise the precision requirements of a DSP algorithm, aiming for efficient implementation in a custom parallel processor. The idea is to trade-off numerical accuracy for area or power-consumption advantages. Again, both analytic and simulation techniques for estimating numerical accuracy are described and contrasted. Optimum and heuristic approaches to precision optimisation are discussed, -A discussion of the importance of the scheduling, allocation, and binding problems, and development of techniques to automate these processes with reference to a precision-optimized algorithm, -Future perspectives for synthesis and optimization of DSP algorithms.


Machine Learning for Signal Processing

Machine Learning for Signal Processing

Author: Max A. Little

Publisher: Oxford University Press, USA

Published: 2019

Total Pages: 378

ISBN-13: 0198714939

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Describes in detail the fundamental mathematics and algorithms of machine learning (an example of artificial intelligence) and signal processing, two of the most important and exciting technologies in the modern information economy. Builds up concepts gradually so that the ideas and algorithms can be implemented in practical software applications.


Mathematical Methods for Signal and Image Analysis and Representation

Mathematical Methods for Signal and Image Analysis and Representation

Author: Luc Florack

Publisher: Springer Science & Business Media

Published: 2012-01-13

Total Pages: 321

ISBN-13: 1447123522

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Mathematical Methods for Signal and Image Analysis and Representation presents the mathematical methodology for generic image analysis tasks. In the context of this book an image may be any m-dimensional empirical signal living on an n-dimensional smooth manifold (typically, but not necessarily, a subset of spacetime). The existing literature on image methodology is rather scattered and often limited to either a deterministic or a statistical point of view. In contrast, this book brings together these seemingly different points of view in order to stress their conceptual relations and formal analogies. Furthermore, it does not focus on specific applications, although some are detailed for the sake of illustration, but on the methodological frameworks on which such applications are built, making it an ideal companion for those seeking a rigorous methodological basis for specific algorithms as well as for those interested in the fundamental methodology per se. Covering many topics at the forefront of current research, including anisotropic diffusion filtering of tensor fields, this book will be of particular interest to graduate and postgraduate students and researchers in the fields of computer vision, medical imaging and visual perception.


Foundations of Signal Processing

Foundations of Signal Processing

Author: Martin Vetterli

Publisher: Cambridge University Press

Published: 2014-09-04

Total Pages: 745

ISBN-13: 1139916572

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This comprehensive and engaging textbook introduces the basic principles and techniques of signal processing, from the fundamental ideas of signals and systems theory to real-world applications. Students are introduced to the powerful foundations of modern signal processing, including the basic geometry of Hilbert space, the mathematics of Fourier transforms, and essentials of sampling, interpolation, approximation and compression The authors discuss real-world issues and hurdles to using these tools, and ways of adapting them to overcome problems of finiteness and localization, the limitations of uncertainty, and computational costs. It includes over 160 homework problems and over 220 worked examples, specifically designed to test and expand students' understanding of the fundamentals of signal processing, and is accompanied by extensive online materials designed to aid learning, including Mathematica® resources and interactive demonstrations.


Linear Algebra for Signal Processing

Linear Algebra for Signal Processing

Author: Adam Bojanczyk

Publisher: Springer Science & Business Media

Published: 2012-12-06

Total Pages: 193

ISBN-13: 1461242282

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Signal processing applications have burgeoned in the past decade. During the same time, signal processing techniques have matured rapidly and now include tools from many areas of mathematics, computer science, physics, and engineering. This trend will continue as many new signal processing applications are opening up in consumer products and communications systems. In particular, signal processing has been making increasingly sophisticated use of linear algebra on both theoretical and algorithmic fronts. This volume gives particular emphasis to exposing broader contexts of the signal processing problems so that the impact of algorithms and hardware can be better understood; it brings together the writings of signal processing engineers, computer engineers, and applied linear algebraists in an exchange of problems, theories, and techniques. This volume will be of interest to both applied mathematicians and engineers.