Digital Signal Processing with Kernel Methods

<p><b> A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems </b> <p><i> Digital Signal Pr...

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Bibliographic Details
Main Authors: Rojo-Álvarez, José Luis, Martínez-Ramón, Manel, Muñoz-Mar&iacute, Jordi, Camps-Valls, Gustau
Format: eBook Book
Language:English
Published: Hoboken, N.J Wiley 2018
Wiley/IEEE Press
John Wiley & Sons, Incorporated
Wiley-IEEE Press
Wiley-Blackwell
John Wiley & Sons (UK)
Edition:1
Series:Wiley - IEEE
Subjects:
Bioengineering
Communication, Networking and Broadcast Technologies
Components, Circuits, Devices and Systems
Computing and Processing
Digital techniques
Fields, Waves and Electromagnetics
Machine learning
Signal processing
Signal processing > Digital techniques
Signal Processing and Analysis
signal processing for multimedia
lvarez
advanced kernel machines
Gustau Camps-Valls
microprocessor electronic systems
digital communications
circuits and linear systems
signal processing for communications
digital signal processing
Digital Signal Processing with Kernel Methods
oz-Mar&iacute
image processing
brain imaging
statistical learning
statistical learning tools
statistical learning theory
signal processing algorithms
signal processing in communications
Jordi Mu&ntilde
signal processing for biomedical engineering systems
machine learning
kernel signal processing
SVM algorithms
Luis Rojo-&Aacute
Manel Mart&iacute
n
introduction to programmable logical devices
digital signal processing models
cardiac signal processing
digital electronic systems
complex system modelling
nez-Ram&oacute
Jos&eacute
ISBN:9781118611791, 1118611799
Online Access:Get full text
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Description
Summary:<p><b> A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems </b> <p><i> Digital Signal Processing with Kernel Methods</i> reviews the milestones in the mixing of classical digital signal processing models and advanced kernel machines statistical learning tools. It explains the fundamental concepts from both fields of machine learning and signal processing so that readers can quickly get up to speed in order to begin developing the concepts and application software in their own research. <p><i> Digital Signal Processing with Kernel Methods</i> provides a comprehensive overview of kernel methods in signal processing, without restriction to any application field. It also offers example applications and detailed benchmarking experiments with real and synthetic datasets throughout. Readers can find further worked examples with Matlab source code on a website developed by the authors. <ul> <li>Presents the necessary basic ideas from both digital signal processing and machine learning concepts</li> <li>Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing</li> <li>Surveys advances in kernel signal processing beyond SVM algorithms to present other highly relevant kernel methods for digital signal processing</li> </ul> <br> <p> An excellent book for signal processing researchers and practitioners, <i>Digital Signal Processing with Kernel Methods</i> will also appeal to those involved in machine learning and pattern recognition.
Bibliography:Includes bibliographical references (p. 589-630) and index
"With website"--P. [1] of cover
ISBN:9781118611791
1118611799
DOI:10.1002/9781118705810