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This four volume set, edited and authored by world leading experts, gives a review of the principles, methods and techniques of important and emerging research topics and technologies in machine learning, advanced signal processing theory, communications and radar signal processing, array and statistical signal processing, Image, Video Processing and Analysis, Hardware, Audio, Acoustic and Speech Processing.
With this reference source you will:
- Quickly grasp a new area of research
- Understand the underlying principles of a topic and its application
- Ascertain how a topic relates to other areas and learn of the research issues yet to be resolved
- Quick tutorial reviews of important and emerging topics of research
- Presents core principles in signal processing theory and shows their application
- Reference content on core principles, technologies, algorithms and applications
- Comprehensive references to journal articles and other literature on which to build further, more specific and detailed knowledge
- Edited by leading people in the field who, through their reputation, have been able to commission experts to write on a particular topic
PhD students, Post Docs, R&D engineers in industry in signal, image, video, speech, acoustic radar, and processing, as well as researchers in wireless and mobile communications
Volume 1: Signal Processing Theory and Machine Learning, Edited by Paulo Sergio Ramirez Diniz (School of Engineering, Rio de Janeiro, Brazil), and Johan Suykens (Katholieke Universiteit Leuven, Brazil)
Volume 2: Communications and Radar Signal Processing, Edited by Nikos Sidiropoulos (Technical University of Crete, Greece), and Fulvio Gini (University of Pisa, Italy)
Volume 3: Array and Statistical Signal Processing, Edited by Abdelhak Zoubir (Technische Universität Darmstadt, Germany) and Mats Viberg (Chalmers University of Technology, Sweden)
Volume 4: Image, Video and Biomedical Signal Processing, Hardware, Acoustic, Audio and Speech Processing, Edited by Joel Trussell (NC State University, North Carolina, USA), Anuj Srivastava (Florida State University, USA) Amit K. Roy Chowdhury (University of California, USA), Ankur Srivastava (University of Maryland, USA) and Patrick Naylor (Imperial College, London, UK).
A representative selection of contributors from all four volumes based in the US, UK, Europe and APAC:
James B. Davis, Auburn University; Philippe Loubaton, Universite de Marne la Vallee; Sergio Barbarossa, University of Rome, Italy; Georgios Giannakis, University of Minnesota, USA; Simon Godsill, Department of Engineering, University of Cambridge, UK; Ali H. Sayed, University of California, USA; William Melvin, Georgia Institute of Technology, USA; Hugh Griffiths, University College London, UK; Stefan V. Baumgartner, Germany; Andrew Carl Singer, College of Engineering, University of Illinois, USA; Fred Harris, San Diego State University, USA; Oscar Au, Hong Kong University of Science and Technolog, Hong Kong, China; James Nagy, Emory Unoversity, USA; Christos Davatzikos, University of Pennsylvania, USA; Al Bovik, The Universtiy of Texas at Austin,Texas, USA; Tsuhan Chen, University of Ithaca, New York, USA; Marylin Wolf, School of ECE, Georgia Institute of Technology, USA; Sven Nordholm, Curtin University, Australia; Visa Koivunen, Aalto University, Finland.
- No. of pages:
- © Academic Press 2013
- 4th October 2013
- Academic Press
- Hardcover ISBN:
Sergios Theodoridis is professor of machine learning and signal processing with the National and Kapodistrian University of Athens, Athens, Greece and with the Chinese University of Hong Kong, Shenzhen, China. He has received a number of prestigious awards, including the 2014 IEEE Signal Processing Magazine Best Paper Award, the 2009 IEEE Computational Intelligence Society Transactions on Neural Networks Outstanding Paper Award, the 2017 European Association for Signal Processing (EURASIP) Athanasios Papoulis Award, the 2014 IEEE Signal Processing Society Education Award, and the 2014 EURASIP Meritorious Service Award. He has served as president of EURASIP and vice president for the IEEE Signal Processing Society and as Editor-in-Chief IEEE Transactions on Signal processing. He is a Fellow of EURASIP and a Life Fellow of IEEE. He is the coauthor of the best selling book Pattern Recognition, 4th edition, Academic Press, 2009 and of the book Introduction to Pattern Recognition: A MATLAB Approach, Academic Press, 2010.
National and Kapodistrian University of Athens, Greece, and Chinese University of Hong Kong, Shenzhen, China.
Prof. Rama Chellappa received the B.E. (Hons.) degree from the University of Madras, India, in 1975 and the M.E. (Distinction) degree from Indian Institute of Science, Bangalore, in 1977. He received M.S.E.E. and Ph.D. Degrees in Electrical Engineering from Purdue University, West Lafayette, IN, in 1978 and 1981 respectively. Since 1991, he has been a Professor of Electrical Engineering and an affiliate Professor of Computer Science at University of Maryland, College Park. He is also affiliated with the Center for Automation Research (Director) and the Institute for Advanced Computer Studies (Permanent Member). In 2005, he was named a Minta Martin Professor of Engineering. Prior to joining the University of Maryland, he was an Assistant (1981-1986) and Associate Professor (1986-1991) and Director of the Signal and Image Processing Institute (1988-1990) at University of Southern California, Los Angeles. Over the last 29 years, he has published numerous book chapters, peer-reviewed journal and conference papers. He has co-authored and edited books on MRFs, face and gait recognition and collected works on image processing and analysis. His current research interests are face and gait analysis, markerless motion capture, 3D modeling from video, image and video-based recognition and exploitation and hyper spectral processing.
University of Maryland, College Park, USA
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