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A realistic and comprehensive review of joint approaches to machine learning and signal processing algorithms, with application to communications, multimedia, and biomedical engineering systems
Digital Signal Processing with Kernel Methods 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.
Digital Signal Processing with Kernel Methods 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: http://github.com/DSPKM
• Presents the necessary basic ideas from both digital signal processing and machine learning concepts
• Reviews the state-of-the-art in SVM algorithms for classification and detection problems in the context of signal processing
• Surveys advances in kernel signal processing beyond SVM algorithms to present other highly relevant kernel methods for digital signal processing
An excellent book for signal processing researchers and practitioners, Digital Signal Processing with Kernel Methods will also appeal to those involved in machine learning and pattern recognition.
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Seitenzahl: 1183
Veröffentlichungsjahr: 2017
José Luis Rojo‐ÁlvarezDepartment of Signal Theory and CommunicationsUniversity Rey Juan CarlosFuenlabrada (Madrid)andCenter for Computational SimulationUniversidad Politécnica de Madrid, Spain
ManelMartínez‐RamónDepartment of Electrical and Computer EngineeringThe University of New MexicoAlbuquerque, New MexicoUSA
JordiMuñoz‐MaríDepartment of Electronics EngineeringUniversitat de ValènciaPaterna (València), Spain
Gustau Camps‐VallsDepartment of Electronics EngineeringUniversitat de ValènciaPaterna (València), Spain
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The right of Jose Luis Rojo‐Alvarez, Manel Martinez‐Ramon, Jordi Munoz‐Mari, Gustau Camps‐Valls to be identified as the authors of the editorial material in this work has been asserted in accordance with law.
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Library of Congress Cataloging‐in‐Publication data
Names: Rojo‐Alvarez, Jose Luis, 1972– author. | Martinez‐Ramon, Manel, 1968– author. | Munoz‐Mari, Jordi, author. | Camps‐Valls, Gustau, 1972– author.Title: Digital signal processing with kernel methods / by Dr. Jose Luis Rojo‐Alvarez, Dr. Manel Martinez‐Ramon, Dr. Jordi Munoz‐Mari, Dr. Gustau Camps‐Valls.Description: First edition. | Hoboken, NJ : John Wiley & Sons, 2018. | Include bibliographical references and index. |Identifiers: LCCN 2017033418 (print) | LCCN 2017044705 (ebook) | ISBN 9781118705827 (pdf) | ISBN 9781118705834 (epub) | ISBN 9781118611791 (cloth)Subjects: LCSH: Signal processing–Digital techniques.Classification: LCC TK5102.9 (ebook) | LCC TK5102.9.R65 2017 (print) | DDC 621.382/20285–dc23LC record available at https://lccn.loc.gov/2017033418
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José Luis Rojo‐Álvarez received the Telecommunication Engineering degree in 1996 from University of Vigo, Spain, and a PhD in Telecommunication Engineering in 2000 from the Polytechnic University of Madrid, Spain. Since 2016, he has been a full Professor in the Department of Signal Theory and Communications, University Rey Juan Carlos, Madrid, Spain. He has published more than 90 papers in indexed journals and more than 150 international conference communications. He has participated in more than 60 projects (with public and private fundings), and directed more than 10 of them, including several actions in the National Plan for Research and Fundamental Science. He was a senior researcher at the Prometeo program in Ecuador (Army University, 2013 to 2015) and research advisor at the Telecommunication Ministry. In 2016 he received the Rey Juan Carlos University Prize for Talented Researcher.
