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Convex Optimization in Signal Processing and Communications (Hardcover)
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Convex Optimization in Signal Processing and Communications (Hardcover)
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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.
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