Read A Rapid Introduction to Adaptive Filtering (SpringerBriefs in Electrical and Computer Engineering)

A Rapid Introduction to Adaptive Filtering (SpringerBriefs in Electrical and Computer Engineering)

Leonardo Rey Vega

4.9/5 (24348 ratings)

Description:In this book, the authors provide insights into the basics of adaptive filtering, which are particularly useful for students taking their first steps into this field. They start by studying the problem of minimum mean-square-error filtering, i.e., Wiener filtering. Then, they analyze iterative methods for solving the optimization problem, e.g., the Method of Steepest Descent. By proposing stochastic approximations, several basic adaptive algorithms are derived, including Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS) and Sign-error algorithms. The authors provide a general framework to study the stability and steady-state performance of these algorithms. The affine Projection Algorithm (APA) which provides faster convergence at the expense of computational complexity (although fast implementations can be used) is also presented. In addition, the Least Squares (LS) method and its recursive version (RLS), including fast implementations are discussed. The book closes with the discussion of several topics of interest in the adaptive filtering field.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with A Rapid Introduction to Adaptive Filtering (SpringerBriefs in Electrical and Computer Engineering). To get started finding A Rapid Introduction to Adaptive Filtering (SpringerBriefs in Electrical and Computer Engineering), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

Pages: 511

Format: PDF, EPUB & Kindle Edition

Publisher: N/A

Release: 2012

ISBN: 3642302998

Description: In this book, the authors provide insights into the basics of adaptive filtering, which are particularly useful for students taking their first steps into this field. They start by studying the problem of minimum mean-square-error filtering, i.e., Wiener filtering. Then, they analyze iterative methods for solving the optimization problem, e.g., the Method of Steepest Descent. By proposing stochastic approximations, several basic adaptive algorithms are derived, including Least Mean Squares (LMS), Normalized Least Mean Squares (NLMS) and Sign-error algorithms. The authors provide a general framework to study the stability and steady-state performance of these algorithms. The affine Projection Algorithm (APA) which provides faster convergence at the expense of computational complexity (although fast implementations can be used) is also presented. In addition, the Least Squares (LS) method and its recursive version (RLS), including fast implementations are discussed. The book closes with the discussion of several topics of interest in the adaptive filtering field.We have made it easy for you to find a PDF Ebooks without any digging. And by having access to our ebooks online or by storing it on your computer, you have convenient answers with A Rapid Introduction to Adaptive Filtering (SpringerBriefs in Electrical and Computer Engineering). To get started finding A Rapid Introduction to Adaptive Filtering (SpringerBriefs in Electrical and Computer Engineering), you are right to find our website which has a comprehensive collection of manuals listed.
Our library is the biggest of these that have literally hundreds of thousands of different products represented.

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A Rapid Introduction to Adaptive Filtering (SpringerBriefs in Electrical and Computer Engineering)

A Rapid Introduction to Adaptive Filtering (SpringerBriefs in Electrical and Computer Engineering)

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