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Digital Signal Processing with Matlab Examples, Volume 3 : Model-Based Actions and Sparse Representation

Digital Signal Processing with Matlab Examples, Volume 3 : Model-Based Actions and Sparse Representation

Digital Signal Processing with Matlab Examples, Volume 3 : Model-Based Actions and Sparse Representation Hardback - 2016

by Jose Maria Giron-Sierra

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Hardcover. New. New Book; Fast Shipping from UK; Not signed; Not First Edition; This is the third volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs. This book inc
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Details

  • Title Digital Signal Processing with Matlab Examples, Volume 3 : Model-Based Actions and Sparse Representation
  • Author Jose Maria Giron-Sierra
  • Binding Hardback
  • Condition New
  • Pages 431
  • Volumes 1
  • Language ENG
  • Publisher Springer
  • Publication date 2016-12-01
  • Illustrated Yes
  • Features Illustrated
  • Bookseller's Inventory # ria9789811025396_inp
  • ISBN 9789811025396 / 9811025398
  • Weight 1.76 lbs (0.80 kg)
  • Dimensions 9.21 x 6.14 x 1 in (23.39 x 15.60 x 2.54 cm)
  • Category Technology & Industrial Arts
  • Dewey Decimal Code 621.382
  • Quantity available 451

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Reader reviews for Digital Signal Processing with Matlab Examples, Volume 3 : Model-Based Actions and Sparse Representation

From the publisher

This is the third volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs.

This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed.

The book primarily focuses on filter banks, wavelets, and images. While the Fourier transform is adequate for periodic signals, wavelets are more suitable for other cases, such as short-duration signals: bursts, spikes, tweets, lung sounds, etc. Both Fourier and wavelet transforms decompose signals into components. Further, both are also invertible, so the original signals can be recovered from their components. Compressedsensing has emerged as a promising idea. One of the intended applications is networked devices or sensors, which are now becoming a reality; accordingly, this topic is also addressed. A selection of experiments that demonstrate image denoising applications are also included. In the interest of reader-friendliness, the longer programs have been grouped in an appendix; further, a second appendix on optimization has been added to supplement the content of the last chapter.

From the rear cover

This is the third volume in a trilogy on modern Signal Processing. The three books provide a concise exposition of signal processing topics, and a guide to support individual practical exploration based on MATLAB programs.

This book includes MATLAB codes to illustrate each of the main steps of the theory, offering a self-contained guide suitable for independent study. The code is embedded in the text, helping readers to put into practice the ideas and methods discussed.

The book primarily focuses on filter banks, wavelets, and images. While the Fourier transform is adequate for periodic signals, wavelets are more suitable for other cases, such as short-duration signals: bursts, spikes, tweets, lung sounds, etc. Both Fourier and wavelet transforms decompose signals into components. Further, both are also invertible, so the original signals can be recovered from their components. Compressed sensing has emerged as a promising idea. One of the intended applications is networked devices or sensors, which are now becoming a reality; accordingly, this topic is also addressed. A selection of experiments that demonstrate image denoising applications are also included. In the interest of reader-friendliness, the longer programs have been grouped in an appendix; further, a second appendix on optimization has been added to supplement the content of the last chapter.

About the author

Prof. Jose M. Giron-Sierra was born in Valladolid, Spain. He receive his Ph.D. in Physics in 1978, Universidad Complutense de Madrid, Spain. Prof. Giron-Sierra wrote more than 160 publications in various international journals. He is IEEE, AIAA, and Eurosim member and belongs to two IFAC Technical Committees.
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