Algorithms for Statistical Signal Processing

Algorithms for Statistical Signal Processing PDF

Author: John G. Proakis

Publisher:

Published: 2002

Total Pages: 584

ISBN-13:

DOWNLOAD EBOOK →

Keeping pace with the expanding, ever more complex applications of DSP, this authoritative presentation of computational algorithms for statistical signal processing focuses on "advanced topics" ignored by other books on the subject. Algorithms for Convolution and DFT. Linear Prediction and Optimum Linear Filters. Least-Squares Methods for System Modeling and Filter Design. Adaptive Filters. Recursive Least-Squares Algorithms for Array Signal Processing. QRD-Based Fast Adaptive Filter Algorithms. Power Spectrum Estimation. Signal Analysis with Higher-Order Spectra. For Electrical Engineers, Computer Engineers, Computer Scientists, and Applied Mathematicians.

Fundamentals of Statistical Signal Processing

Fundamentals of Statistical Signal Processing PDF

Author: Steven M. Kay

Publisher: Pearson Education

Published: 2013

Total Pages: 496

ISBN-13: 013280803X

DOWNLOAD EBOOK →

"For those involved in the design and implementation of signal processing algorithms, this book strikes a balance between highly theoretical expositions and the more practical treatments, covering only those approaches necessary for obtaining an optimal estimator and analyzing its performance. Author Steven M. Kay discusses classical estimation followed by Bayesian estimation, and illustrates the theory with numerous pedagogical and real-world examples."--Cover, volume 1.

Machine Learning for Signal Processing

Machine Learning for Signal Processing PDF

Author: Max A. Little

Publisher: Oxford University Press, USA

Published: 2019

Total Pages: 378

ISBN-13: 0198714939

DOWNLOAD EBOOK →

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.

An Introduction to Statistical Signal Processing

An Introduction to Statistical Signal Processing PDF

Author: Robert M. Gray

Publisher: Cambridge University Press

Published: 2004-12-02

Total Pages: 479

ISBN-13: 1139456288

DOWNLOAD EBOOK →

This book describes the essential tools and techniques of statistical signal processing. At every stage theoretical ideas are linked to specific applications in communications and signal processing using a range of carefully chosen examples. The book begins with a development of basic probability, random objects, expectation, and second order moment theory followed by a wide variety of examples of the most popular random process models and their basic uses and properties. Specific applications to the analysis of random signals and systems for communicating, estimating, detecting, modulating, and other processing of signals are interspersed throughout the book. Hundreds of homework problems are included and the book is ideal for graduate students of electrical engineering and applied mathematics. It is also a useful reference for researchers in signal processing and communications.

Statistical Signal Processing

Statistical Signal Processing PDF

Author: Swagata Nandi

Publisher: Springer Nature

Published: 2020-08-21

Total Pages: 265

ISBN-13: 9811562806

DOWNLOAD EBOOK →

This book introduces readers to various signal processing models that have been used in analyzing periodic data, and discusses the statistical and computational methods involved. Signal processing can broadly be considered to be the recovery of information from physical observations. The received signals are usually disturbed by thermal, electrical, atmospheric or intentional interferences, and due to their random nature, statistical techniques play an important role in their analysis. Statistics is also used in the formulation of appropriate models to describe the behavior of systems, the development of appropriate techniques for estimation of model parameters and the assessment of the model performances. Analyzing different real-world data sets to illustrate how different models can be used in practice, and highlighting open problems for future research, the book is a valuable resource for senior undergraduate and graduate students specializing in mathematics or statistics.

Statistical Digital Signal Processing and Modeling

Statistical Digital Signal Processing and Modeling PDF

Author: Monson H. Hayes

Publisher: John Wiley & Sons

Published: 1996-04-19

Total Pages: 629

ISBN-13: 0471594318

DOWNLOAD EBOOK →

The main thrust is to provide students with a solid understanding of a number of important and related advanced topics in digital signal processing such as Wiener filters, power spectrum estimation, signal modeling and adaptive filtering. Scores of worked examples illustrate fine points, compare techniques and algorithms and facilitate comprehension of fundamental concepts. Also features an abundance of interesting and challenging problems at the end of every chapter.

Digital Signal Processing and Statistical Classification

Digital Signal Processing and Statistical Classification PDF

Author: George J. Miao

Publisher: Artech House

Published: 2002

Total Pages: 522

ISBN-13: 9781580531351

DOWNLOAD EBOOK →

This is the first book to introduce and integrate advanced digital signal processing (DSP) and classification together, and the only volume to introduce state-of-the-art transforms including DFT, FFT, DCT, DHT, PCT, CDT, and ODT together for DSP and communication applications. You get step-by-step guidance in discrete-time domain signal processing and frequency domain signal analysis; digital filter design and adaptive filtering; multirate digital processing; and statistical signal classification. It also helps you overcome problems associated with multirate A/D and D/A converters.

Statistical Signal Processing of Complex-Valued Data

Statistical Signal Processing of Complex-Valued Data PDF

Author: Peter J. Schreier

Publisher: Cambridge University Press

Published: 2010-02-04

Total Pages: 331

ISBN-13: 1139487620

DOWNLOAD EBOOK →

Complex-valued random signals are embedded in the very fabric of science and engineering, yet the usual assumptions made about their statistical behavior are often a poor representation of the underlying physics. This book deals with improper and noncircular complex signals, which do not conform to classical assumptions, and it demonstrates how correct treatment of these signals can have significant payoffs. The book begins with detailed coverage of the fundamental theory and presents a variety of tools and algorithms for dealing with improper and noncircular signals. It provides a comprehensive account of the main applications, covering detection, estimation, and signal analysis of stationary, nonstationary, and cyclostationary processes. Providing a systematic development from the origin of complex signals to their probabilistic description makes the theory accessible to newcomers. This book is ideal for graduate students and researchers working with complex data in a range of research areas from communications to oceanography.

Lanterna Rally - Theme by Grace Themes