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Convex Optimization in Signal Processing and Communications

Convex Optimization in Signal Processing and Communications

by Daniel P. Palomar and Yonina C. Eldar
Hardback
Publication Date: 03/12/2009

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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.
ISBN:
9780521762229
9780521762229
Category:
Communications engineering / telecommunications
Format:
Hardback
Publication Date:
03-12-2009
Language:
English
Publisher:
Cambridge University Press
Country of origin:
United Kingdom
Pages:
512
Dimensions (mm):
255x185x29mm
Weight:
1.14kg

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