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      Digital Signal Processing with Examples in MATLAB®
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      Book

      Digital Signal Processing with Examples in MATLAB®

      DOI link for Digital Signal Processing with Examples in MATLAB®

      Digital Signal Processing with Examples in MATLAB® book

      Digital Signal Processing with Examples in MATLAB®

      DOI link for Digital Signal Processing with Examples in MATLAB®

      Digital Signal Processing with Examples in MATLAB® book

      BySamuel D. Stearns, Don R. Hush
      Edition 2nd Edition
      First Published 2011
      eBook Published 5 November 2012
      Pub. Location Boca Raton
      Imprint CRC Press
      DOI https://doi.org/10.1201/9781439837832
      Pages 516
      eBook ISBN 9780429106132
      Subjects Engineering & Technology
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      Stearns, S.D., & Hush, D.R. (2011). Digital Signal Processing with Examples in MATLAB® (2nd ed.). CRC Press. https://doi.org/10.1201/9781439837832

      ABSTRACT

      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

      TABLE OF CONTENTS

      chapter 1|18 pages

      Introduction

      chapter 2|19 pages

      Least Squares, Orthogonality, and the Fourier Series

      chapter 3|50 pages

      Correlation, Fourier Spectra, and the Sampling Theorem

      chapter 4|48 pages

      Linear Systems and Transfer Functions

      chapter 5|24 pages

      FIR Filter Design

      chapter 6|38 pages

      IIR Filter Design

      chapter 7|32 pages

      Random Signals and Spectral Estimation

      chapter 8|42 pages

      Least-Squares System Design

      chapter 9|36 pages

      Adaptive Signal Processing

      chapter 10|54 pages

      Signal Information, Coding, and Compression

      chapter 11|40 pages

      Models of Analog Systems

      chapter 12|50 pages

      Pattern Recognition with Support Vector Machines

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