Mathematical Methods and Algorithms for Signal Processing
Author | : Todd K. Moon |
Publisher | : Pearson |
Total Pages | : 990 |
Release | : 2000 |
Genre | : Computers |
ISBN | : |
This previously included a CD. The CD contents can be accessed via World Wide Web.
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Author | : Todd K. Moon |
Publisher | : Pearson |
Total Pages | : 990 |
Release | : 2000 |
Genre | : Computers |
ISBN | : |
This previously included a CD. The CD contents can be accessed via World Wide Web.
Author | : Richard E. Blahut |
Publisher | : Cambridge University Press |
Total Pages | : 469 |
Release | : 2010-06-24 |
Genre | : Technology & Engineering |
ISBN | : 1139487957 |
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.
Author | : Erchin Serpedin |
Publisher | : CRC Press |
Total Pages | : 852 |
Release | : 2017-12-04 |
Genre | : Computers |
ISBN | : 1439855145 |
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.
Author | : Charles L. Byrne |
Publisher | : CRC Press |
Total Pages | : 441 |
Release | : 2014-11-12 |
Genre | : Computers |
ISBN | : 1482241846 |
Signal Processing: A Mathematical Approach is designed to show how many of the mathematical tools the reader knows can be used to understand and employ signal processing techniques in an applied environment. Assuming an advanced undergraduate- or graduate-level understanding of mathematics—including familiarity with Fourier series, matrices, probability, and statistics—this Second Edition: Contains new chapters on convolution and the vector DFT, plane-wave propagation, and the BLUE and Kalman filters Expands the material on Fourier analysis to three new chapters to provide additional background information Presents real-world examples of applications that demonstrate how mathematics is used in remote sensing Featuring problems for use in the classroom or practice, Signal Processing: A Mathematical Approach, Second Edition covers topics such as Fourier series and transforms in one and several variables; applications to acoustic and electro-magnetic propagation models, transmission and emission tomography, and image reconstruction; sampling and the limited data problem; matrix methods, singular value decomposition, and data compression; optimization techniques in signal and image reconstruction from projections; autocorrelations and power spectra; high-resolution methods; detection and optimal filtering; and eigenvector-based methods for array processing and statistical filtering, time-frequency analysis, and wavelets.
Author | : Jonathan M Blackledge |
Publisher | : Elsevier |
Total Pages | : 840 |
Release | : 2006-03-01 |
Genre | : Technology & Engineering |
ISBN | : 0857099450 |
This book forms the first part of a complete MSc course in an area that is fundamental to the continuing revolution in information technology and communication systems. Massively exhaustive, authoritative, comprehensive and reinforced with software, this is an introduction to modern methods in the developing field of Digital Signal Processing (DSP). The focus is on the design of algorithms and the processing of digital signals in areas of communications and control, providing the reader with a comprehensive introduction to the underlying principles and mathematical models. - Provides an introduction to modern methods in the developing field of Digital Signal Processing (DSP) - Focuses on the design of algorithms and the processing of digital signals in areas of communications and control - Provides a comprehensive introduction to the underlying principles and mathematical models of Digital Signal Processing
Author | : Todd K. Moon |
Publisher | : John Wiley & Sons |
Total Pages | : 800 |
Release | : 2005-06-06 |
Genre | : Computers |
ISBN | : 0471648000 |
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.
Author | : Allen B. Downey |
Publisher | : "O'Reilly Media, Inc." |
Total Pages | : 172 |
Release | : 2016-07-12 |
Genre | : Technology & Engineering |
ISBN | : 149193851X |
If you understand basic mathematics and know how to program with Python, you’re ready to dive into signal processing. While most resources start with theory to teach this complex subject, this practical book introduces techniques by showing you how they’re applied in the real world. In the first chapter alone, you’ll be able to decompose a sound into its harmonics, modify the harmonics, and generate new sounds. Author Allen Downey explains techniques such as spectral decomposition, filtering, convolution, and the Fast Fourier Transform. This book also provides exercises and code examples to help you understand the material. You’ll explore: Periodic signals and their spectrums Harmonic structure of simple waveforms Chirps and other sounds whose spectrum changes over time Noise signals and natural sources of noise The autocorrelation function for estimating pitch The discrete cosine transform (DCT) for compression The Fast Fourier Transform for spectral analysis Relating operations in time to filters in the frequency domain Linear time-invariant (LTI) system theory Amplitude modulation (AM) used in radio Other books in this series include Think Stats and Think Bayes, also by Allen Downey.
Author | : Steven B. Damelin |
Publisher | : Cambridge University Press |
Total Pages | : 463 |
Release | : 2012 |
Genre | : Mathematics |
ISBN | : 1107013224 |
Develops mathematical and probabilistic tools needed to give rigorous derivations and applications of fundamental results in signal processing theory.
Author | : J. G. McWhirter |
Publisher | : Oxford University Press, USA |
Total Pages | : 848 |
Release | : 1990 |
Genre | : Language Arts & Disciplines |
ISBN | : |
This volume presents recent advances in signal processing, an area that involves the application of a wide variety of mathematical methods ranging from adaptive filtering and spectral analysis to finite fields and statistics. The book provides state-of-the-art coverage of such areas as coding and cryptography, inverse problems and image processing, and linear algebra. Special attention is paid to the development and implementation of new parallel algorithms in signal processing.