Digital Signal Processing with Examples in MATLAB®
Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today's powerful computing capabilities, they can be used in a wide range of application areas, including engineering, communicati
1137044228
Digital Signal Processing with Examples in MATLAB®
Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today's powerful computing capabilities, they can be used in a wide range of application areas, including engineering, communicati
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Digital Signal Processing with Examples in MATLAB®

Digital Signal Processing with Examples in MATLAB®

Digital Signal Processing with Examples in MATLAB®
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Digital Signal Processing with Examples in MATLAB®

Digital Signal Processing with Examples in MATLAB®

Overview

Based on fundamental principles from mathematics, linear systems, and signal analysis, digital signal processing (DSP) algorithms are useful for extracting information from signals collected all around us. Combined with today's powerful computing capabilities, they can be used in a wide range of application areas, including engineering, communicati

Product Details

ISBN-13: 9781000755633
Publisher: CRC Press
Publication date: 04/19/2016
Series: Electrical Engineering & Applied Signal Processing Series
Sold by: Barnes & Noble
Format: eBook
Pages: 516
File size: 13 MB
Note: This product may take a few minutes to download.

About the Author

Samuel D. Stearns is a professor emeritus at the University of New Mexico, where has been involved in adjunct teaching and research since 1960. An IEEE fellow, Dr. Stearns was also a distinguished member of the technical staff at Sandia National Laboratories for 27 years. His principal technical areas are DSP and adaptive signal processing.

Don R. Hush is a technical staff member at the Los Alamos National Laboratory. An IEEE senior member, Dr. Hush was previously a technical staff member at Sandia National Laboratories and a professor at the University of New Mexico. He was also an associate editor for IEEE Transactions on Neural Networks and IEEE Signal Processing Magazine.

Table of Contents

Introduction. Least Squares, Orthogonality, and the Fourier Series. Correlation, Fourier Spectra, and the Sampling Theorem. Linear Systems and Transfer Functions. Finite Impulse Response Filter Design. Infinite Impulse Response Filter Design. Random Signals and Spectral Estimation. Least-Squares System Design. Adaptive Signal Processing. Signal Information, Coding, and Compression. Models of Analog Systems. Pattern Recognition with Support Vector Machines. Appendix. Index.
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Science & Technology
Computers
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Electronics - General & Miscellaneous
Engineering - Electrical & Electronic
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Simulation & Modeling - Software Engineering
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