220,59 €
Adaptive Filtering
Adaptive Filtering
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Adaptive Filtering
Adaptive Filtering
El. knyga:
220,59 €
Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB(r) covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area the least mean square (LMS) adaptive filter.This largely self-contained text:Discusses random variables, stochastic processes, vectors, matrices, determinants, discrete ra…

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Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB(r) covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area the least mean square (LMS) adaptive filter.

This largely self-contained text:


Discusses random variables, stochastic processes, vectors, matrices, determinants, discrete random signals, and probability distributions Explains how to find the eigenvalues and eigenvectors of a matrix and the properties of the error surfaces Explores the Wiener filter and its practical uses, details the steepest descent method, and develops the Newton s algorithm Addresses the basics of the LMS adaptive filter algorithm, considers LMS adaptive filter variants, and provides numerous examples Delivers a concise introduction to MATLAB(r), supplying problems, computer experiments, and more than 110 functions and script files
Featuring robust appendices complete with mathematical tables and formulas, Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB(r) clearly describes the key principles of adaptive filtering and effectively demonstrates how to apply them to solve real-world problems."

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Adaptive filters are used in many diverse applications, appearing in everything from military instruments to cellphones and home appliances. Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB(r) covers the core concepts of this important field, focusing on a vital part of the statistical signal processing area the least mean square (LMS) adaptive filter.

This largely self-contained text:


Discusses random variables, stochastic processes, vectors, matrices, determinants, discrete random signals, and probability distributions Explains how to find the eigenvalues and eigenvectors of a matrix and the properties of the error surfaces Explores the Wiener filter and its practical uses, details the steepest descent method, and develops the Newton s algorithm Addresses the basics of the LMS adaptive filter algorithm, considers LMS adaptive filter variants, and provides numerous examples Delivers a concise introduction to MATLAB(r), supplying problems, computer experiments, and more than 110 functions and script files
Featuring robust appendices complete with mathematical tables and formulas, Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB(r) clearly describes the key principles of adaptive filtering and effectively demonstrates how to apply them to solve real-world problems."

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