Mathematical Methods and Algorithms for Signal Processing
Author: Todd K. Moon
Publisher: Pearson
Published: 2000
Total Pages: 990
ISBN-13:
DOWNLOAD EBOOKThis previously included a CD. The CD contents can be accessed via World Wide Web.
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Mathematical Methods and Algorithms for Signal Processing(Paperback)
Author: Moon
Publisher:
Published: 2000-01-01
Total Pages: 937
ISBN-13: 9788945006424
DOWNLOAD EBOOKFast Algorithms for Signal Processing
Author: Richard E. Blahut
Publisher: Cambridge University Press
Published: 2010-06-24
Total Pages: 469
ISBN-13: 1139487957
DOWNLOAD EBOOKEfficient 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.
Signal Processing
Author: Charles L. Byrne
Publisher: CRC Press
Published: 2014-11-12
Total Pages: 441
ISBN-13: 1482241846
DOWNLOAD EBOOKSignal 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.
Mathematical Foundations for Signal Processing, Communications, and Networking
Author: Erchin Serpedin
Publisher: CRC Press
Published: 2017-12-04
Total Pages: 852
ISBN-13: 1439855145
DOWNLOAD EBOOKMathematical 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.
Foundations of Signal Processing
Author: Martin Vetterli
Publisher: Cambridge University Press
Published: 2014-09-04
Total Pages: 745
ISBN-13: 1139916572
DOWNLOAD EBOOKThis 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.
Think DSP
Author: Allen B. Downey
Publisher: "O'Reilly Media, Inc."
Published: 2016-07-12
Total Pages: 172
ISBN-13: 149193851X
DOWNLOAD EBOOKIf 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.
The Mathematics of Signal Processing
Author: Steven B. Damelin
Publisher: Cambridge University Press
Published: 2012
Total Pages: 463
ISBN-13: 1107013224
DOWNLOAD EBOOKDevelops mathematical and probabilistic tools needed to give rigorous derivations and applications of fundamental results in signal processing theory.
Mathematics in Signal Processing II
Author: J. G. McWhirter
Publisher: Oxford University Press, USA
Published: 1990
Total Pages: 848
ISBN-13:
DOWNLOAD EBOOKThis 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.
Valuepack
Author: Prokais
Publisher: Prentice Hall
Published: 2005-07-27
Total Pages:
ISBN-13: 9781405825603
DOWNLOAD EBOOKDigital Signal Processing: Principles, Algorithms and Applications: International Edition, 3/e Suitable for a one- or two-semester undergraduate-level electrical engineering, computer engineering, and computer science course in Discrete Systems and Digital Signal Processing. Assumes some prior knowledge of advanced calculus, linear systems for continuous-time signals, and Fourier series and transforms. Giving students a sound balance of theory and practical application, this no-nonsense text presents the fundamental concepts and techniques of modern digital signal processing with related algorithms and applications. Covering both time-domain and frequency- domain methods for the analysis of linear, discrete-time systems, the book offers cutting-edge coverage on such topics as sampling, digital filter design, filter realizations, deconvolution, interpolation, decimation, state-space methods, spectrum analysis, and more. Rigorous and challenging, it further prepares students with numerous examples, exercises, and experiments emphasizing software implementation of digital signal processing algorithms integrated throughout. Introduction to Wavelets and Wavelet Transforms: A Primer, 1/e Advanced undergraduate and beginning graduate students, faculty, researchers and practitioners in signal processing, telecommunications, and computer science, and applied mathematics. It assumes a background of Fourier series and transforms and of linear algebra and matrix methods. This primer presents a well balanced blend of the mathematical theory underlying wavelet techniques and a discussion that gives insight into why wavelets are successful in signal analysis, compression, dection, numerical analysis, and a wide variety of other theoretical and practical applications. It fills a gap in the existing wavelet literature with its unified view of expansions of signals into bases and frames, as well as the use of filter banks as descriptions and algorithms.
