Convex Optimization In Signal Processing And Communications - Daniel P. Palomar, Yonina C. Eldar
Cambridge University Press (2009)
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Convex functions, Mathematical optimization, Mathematics / Functional Analysis, Mathematics / Mathematical Analysis, Signal processing

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 optimization for networked systems, cognitive radio systems via game theory, and the variational inequality approach for Nash equilibrium solutions.

Product Details
LoC Classification TK5102.9 .C587 2010
Dewey 621.3822015196
No. of Pages 512
Height x Width 247 x 174 mm