Academic Press Library in Signal Processing: Array and Statistical Signal Processing

by Mats Viberg (Editor), Abdelhak Zoubir (Editor), Sergios Theodoridis (Editor), Rama Chellappa (Editor)

Overview

This third volume, 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 array and statistical signal 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 in array and statistical signal processing - Presents core principles 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

Product Details

ISBN-13:	9780124116214
Publisher:	Elsevier Science & Technology Books
Publication date:	08/31/2013
Series:	Academic Press Library in Signal Processing , #3
Sold by:	Barnes & Noble
Format:	eBook
Pages:	1012
File size:	32 MB
Note:	This product may take a few minutes to download.

About the Author

Sergios Theodoridis is professor emeritus of machine learning and data processing with the National and Kapodistrian University of Athens, Athens, Greece. He has also served as distinguished professor with the Aalborg University Denmark and as professor with the Chinese University of Hong Kong, Shenzhen, China. In 2023, he received an honorary doctorate degree (D.Sc) from the University of Edinburgh, U.K. He has also 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 Carl Friedrich Gauss 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. He is a Fellow of EURASIP and a Life Fellow of IEEE. He is the coauthor of the book Pattern Recognition, 4th edition, Academic Press, 2009 and of the book Introduction to Pattern Recognition: A MATLAB Approach, Academic Press, 2010.
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.

Table of Contents

Introduction to Statistical Signal Processing; Model Order Selection; Non-Stationary Signal Analysis Time-Frequency Approach; Bayesian Computational Methods in Signal Processing; Distributed Signal Detection; Quickest Change Detection; Geolocation—Maps, Measurements, Models, and Methods; Performance Analysis and Bounds; Diffusion Adaptation Over Networks; Array Signal Processing: Overview of the Included Chapters; ntroduction to Array Processing; Adaptive and Robust Beamforming; Broadband Beamforming and Optimization; DOA Estimation Methods and Algorithms; Subspace Methods and Exploitation of Special Array Structures; Performance Bounds and Statistical Analysis of DOA Estimation; DOA Estimation of Nonstationary Signals; Source Localization and Tracking; Array Processing in the Face of Nonidealities; Applications of Array Signal Processing