Convex optimization in signal processing and communications

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 andon 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. INDICE: 1. Automatic code generation for real-time convex optimization J. Mattingley and S. Boyd; 2. Gradient-based algorithms with applications to signal recovery problems A. Beck and M. Teboulle; 3. Graphical models of autoregressive processes J. Songsiri, J. Dahl and L. Vandenberghe; 4. SDP relaxation ofhomogeneous quadratic optimization Z. Q. Luo and T. H. Chang; 5. Probabilistic analysis of SDR detectors for MIMO systems A. Man-Cho So and Y. Ye; 6. Semidefinite programming, matrix decomposition, and radar code design Y. Huang, A. De Maio and S. Zhang; 7. Convex analysis for non-negative blind source separation with application in imaging W. K. Ma, T. H. Chan, C. Y. Chi and Y. Wang; 8. Optimization techniques in modern sampling theory T. Michaeli and Y. C. Eldar; 9. Robust broadband adaptive beamforming using convex optimization M. Rubsamen, A. El-Keyi, A. B. Gershman and T. Kirubarajan; 10. Cooperative distributed multi-agent optimization A. Nenadi and A. Ozdaglar; 11. Competitive optimization of cognitive radio MIMO systems via game theory G. Scutari, D. P. Palomarand S. Barbarossa; 12. Nash equilibria: the variational approach F. Facchineiand J. S. Pang

• ISBN: 978-0-521-76222-9
• Editorial: Cambridge University Press
• Encuadernacion: Cartoné
• Páginas: 512
• Fecha Publicación: 03/12/2009
• Nº Volúmenes: 1
• Idioma: Inglés