Algorithms For Statistical Signal Processing
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Author |
: John G. Proakis |
Publisher |
: |
Total Pages |
: 584 |
Release |
: 2002 |
ISBN-10 |
: UOM:39015053184167 |
ISBN-13 |
: |
Rating |
: 4/5 (67 Downloads) |
Synopsis Algorithms for Statistical Signal Processing by : John G. Proakis
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.
Author |
: J.G.·普罗基斯 |
Publisher |
: |
Total Pages |
: 567 |
Release |
: 2003 |
ISBN-10 |
: 7302061696 |
ISBN-13 |
: 9787302061694 |
Rating |
: 4/5 (96 Downloads) |
Synopsis 统计信号处理算法 by : J.G.·普罗基斯
著者译名:普罗基斯。
Author |
: Steven M. Kay |
Publisher |
: Pearson Education |
Total Pages |
: 496 |
Release |
: 2013 |
ISBN-10 |
: 9780132808033 |
ISBN-13 |
: 013280803X |
Rating |
: 4/5 (33 Downloads) |
Synopsis Fundamentals of Statistical Signal Processing by : Steven M. Kay
"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.
Author |
: Max A. Little |
Publisher |
: Oxford University Press, USA |
Total Pages |
: 378 |
Release |
: 2019 |
ISBN-10 |
: 9780198714934 |
ISBN-13 |
: 0198714939 |
Rating |
: 4/5 (34 Downloads) |
Synopsis Machine Learning for Signal Processing by : Max A. Little
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.
Author |
: Swagata Nandi |
Publisher |
: Springer Nature |
Total Pages |
: 265 |
Release |
: 2020-08-21 |
ISBN-10 |
: 9789811562808 |
ISBN-13 |
: 9811562806 |
Rating |
: 4/5 (08 Downloads) |
Synopsis Statistical Signal Processing by : Swagata Nandi
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.
Author |
: Monson H. Hayes |
Publisher |
: John Wiley & Sons |
Total Pages |
: 629 |
Release |
: 1996-04-19 |
ISBN-10 |
: 9780471594314 |
ISBN-13 |
: 0471594318 |
Rating |
: 4/5 (14 Downloads) |
Synopsis Statistical Digital Signal Processing and Modeling by : Monson H. Hayes
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.
Author |
: Robert M. Gray |
Publisher |
: Cambridge University Press |
Total Pages |
: 479 |
Release |
: 2004-12-02 |
ISBN-10 |
: 9781139456289 |
ISBN-13 |
: 1139456288 |
Rating |
: 4/5 (89 Downloads) |
Synopsis An Introduction to Statistical Signal Processing by : Robert M. Gray
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.
Author |
: Phillip Allen Rhodes |
Publisher |
: |
Total Pages |
: 142 |
Release |
: 2000 |
ISBN-10 |
: OCLC:46772811 |
ISBN-13 |
: |
Rating |
: 4/5 (11 Downloads) |
Synopsis Statistical Signal Processing Algorithms by : Phillip Allen Rhodes
Author |
: Mats Viberg |
Publisher |
: Academic Press |
Total Pages |
: 1013 |
Release |
: 2013-08-31 |
ISBN-10 |
: 9780124116214 |
ISBN-13 |
: 0124116213 |
Rating |
: 4/5 (14 Downloads) |
Synopsis Academic Press Library in Signal Processing by : Mats Viberg
This third volume, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in array and statistical signal processing. With this reference source you will: - Quickly grasp a new area of research - Understand the underlying principles of a topic and its application - Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved - Quick tutorial reviews of important and emerging topics of research in array and statistical signal processing - Presents core principles and shows their application - Reference content on core principles, technologies, algorithms and applications - Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge - Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
Author |
: Tianshuang Qiu |
Publisher |
: Walter de Gruyter GmbH & Co KG |
Total Pages |
: 602 |
Release |
: 2018-07-09 |
ISBN-10 |
: 9783110465082 |
ISBN-13 |
: 3110465086 |
Rating |
: 4/5 (82 Downloads) |
Synopsis Signal Processing and Data Analysis by : Tianshuang Qiu
This book presents digital signal processing theories and methods and their applications in data analysis, error analysis and statistical signal processing. Algorithms and Matlab programming are included to guide readers step by step in dealing with practical difficulties. Designed in a self-contained way, the book is suitable for graduate students in electrical engineering, information science and engineering in general.