Adaptive Filtering: Fundamentals of Least Mean Squares with MATLAB®

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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® 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®, 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® 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 Filtering: Fundamentals of Least Mean Squares with MATLAB®
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Paperback: 363 pages
Publisher: CRC Press; 1 edition (September 26, 2014)
Language: English
ISBN-10: 1482253356
ISBN-13: 978-1482253351
Product Dimensions: 0.8 x 6 x 8.8 inches
Shipping Weight: 1 pounds

• http://www.amazon.com/Adaptive-Filtering-Fundamentals-Squares-MATLAB%C2%AE/dp/1482253356/ref=sr_1_1_twi_1?ie=UTF8&qid=1424227903&sr=8-1&keywords=Adaptive+Filtering%3A+Fundamentals+of+Least+Mean+Squares+with+MATLAB%C2%AE
  

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