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Academic Press Library in Signal Processing, Volume 7: Array, Radar and Communications Engineering is aimed at university researchers, post graduate students and R&D engineers in the industry, providing a tutorial-based, comprehensive review of key topics and technologies of research in Array and Radar Processing, Communications Engineering and Machine Learning. Users will find the book to be an invaluable starting point to their research and initiatives.
With this reference, readers will quickly grasp an unfamiliar area of research, understand the underlying principles of a topic, learn how a topic relates to other areas, and learn of research issues yet to be resolved.
- Presents a quick tutorial of reviews of important and emerging topics of research
- Explores core principles, technologies, algorithms and applications
- Edited and contributed by international leading figures in the field
- Includes comprehensive references to journal articles and other literature upon which to build further, more detailed knowledge
Engineers who use signal processing for arrays, Radars, Bayesian learning, deep Learning, MIMO, Speech enhancement, Machine Learning
1. Holistic Radar Waveform Diversity
2. Geometric Algebra for Radar Detection
3. Cognitive Radar Techniques for Next Generation Radar Systems
4. Parameter Bounds Under Misspecified Models for Adaptive Radar Detection
5. Multistatic Radar Systems
6. Sparsity-Based Radar Techniques
7. mmWave radar systems and techniques
8. Signal Processing for Massive MIMO Communications
9. Distributed Beamforming
10. Transmit Beamforming for Wireless Power and Information Transfer
11. Sparse Methods for Direction-of-Arrival Estimation
12. Beamforming Techniques using Microphone Arrays
- No. of pages:
- © Academic Press 2018
- 17th November 2017
- Academic Press
- Paperback ISBN:
- eBook ISBN:
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
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.
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