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Cambridge University Press, 2009-12-03. Hardcover. Very Good. 2.7919 24.8731 18.0203. Unread. There is some minor wear to the cover.
Convex Optimization in Signal Processing and Communications by Palomar, Daniel P. (Editor)/ Eldar, Yonina C. (Editor) - 2009
by Palomar, Daniel P. (Editor)/ Eldar, Yonina C. (Editor)
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Convex Optimization in Signal Processing and Communications
by Palomar, Daniel P. (Editor)/ Eldar, Yonina C. (Editor)
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Cambridge Univ Pr, 2009. Hardcover. New. 1st edition. 520 pages. 7.72x4.57x0.47 inches.
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- ISBN 10 0521762227
- ISBN 13 9780521762229
- Publisher Cambridge Univ Pr
- Date Published 2009
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Convex Optimization in Signal Processing and Communications
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Convex Optimization in Signal Processing and Communications by Palomar, Daniel P.
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ISBN: 9780521762229CAMBRIDGE UNIVERSITY PRESS | 25 January 2010
Hardback | 512 pages
Over the past two decades there have been significant advances in the field of optimization. In particular, convex optimization has emerged as a powerful signal processing tool, and the variety of applications continues to grow rapidly. This book, written by a team of leading experts, sets out the theoretical underpinnings of the subject and provides tutorials on a wide range of convex optimization applications. Emphasis throughout is on cutting-edge research and on formulating problems in convex form, making this an ideal textbook for advanced graduate courses and a useful self-study guide. Topics covered range from automatic code generation, graphical models, and gradient-based algorithms for signal recovery, to semidefinite programming (SDP) relaxation and radar waveform design via SDP. It also includes blind source separation for image processing, robust broadband beamforming, distributed multi-agent… Read More
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Convex Optimization in Signal Processing and Communications
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Cambridge University Press, 2009-12-03. Hardcover. New. 2.7919 24.8731 18.0203.
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Convex Optimization in Signal Processing and Communications
by Daniel P. Palomar
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Hardback. New. Leading experts provide the theoretical underpinnings of the subject plus tutorials on a wide range of applications, from automatic code generation to robust broadband beamforming. Emphasis on cutting-edge research and formulating problems in convex form make this an ideal textbook for advanced graduate courses and a useful self-study guide.
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