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Digital signal processing with Matlab examples

This is the first 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 t...

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Detalles Bibliográficos
Autor principal: Giron-Sierra, Jose Maria
Lenguaje:eng
Publicado: Springer 2017
Materias:
Acceso en línea:https://dx.doi.org/10.1007/978-981-10-2534-1
https://dx.doi.org/10.1007/978-981-10-2537-2
https://dx.doi.org/10.1007/978-981-10-2540-2
http://cds.cern.ch/record/2240649
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author Giron-Sierra, Jose Maria
author_facet Giron-Sierra, Jose Maria
author_sort Giron-Sierra, Jose Maria
collection CERN
description This is the first 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 is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.
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spelling cern-22406492021-04-21T19:23:20Zdoi:10.1007/978-981-10-2534-1doi:10.1007/978-981-10-2537-2doi:10.1007/978-981-10-2540-2http://cds.cern.ch/record/2240649engGiron-Sierra, Jose MariaDigital signal processing with Matlab examplesEngineeringThis is the first 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 is divided into three parts, the first of which introduces readers to periodic and non-periodic signals. The second part is devoted to filtering, which is an important and commonly used application. The third part addresses more advanced topics, including the analysis of real-world non-stationary signals and data, e.g. structural fatigue, earthquakes, electro-encephalograms, birdsong, etc. The book’s last chapter focuses on modulation, an example of the intentional use of non-stationary signals.This is the second 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 second book focuses on recent developments in response to the demands of new digital technologies. It is divided into two parts: the first part includes four chapters on the decomposition and recovery of signals, with special emphasis on images. In turn, the second part includes three chapters and addresses important data-based actions, such as adaptive filtering, experimental modeling, and classification. .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.Springeroai:cds.cern.ch:22406492017
spellingShingle Engineering
Giron-Sierra, Jose Maria
Digital signal processing with Matlab examples
title Digital signal processing with Matlab examples
title_full Digital signal processing with Matlab examples
title_fullStr Digital signal processing with Matlab examples
title_full_unstemmed Digital signal processing with Matlab examples
title_short Digital signal processing with Matlab examples
title_sort digital signal processing with matlab examples
topic Engineering
url https://dx.doi.org/10.1007/978-981-10-2534-1
https://dx.doi.org/10.1007/978-981-10-2537-2
https://dx.doi.org/10.1007/978-981-10-2540-2
http://cds.cern.ch/record/2240649
work_keys_str_mv AT gironsierrajosemaria digitalsignalprocessingwithmatlabexamples