Convex Optimization in Signal Processing and Communications
Herausgeber: Palomar, Daniel P; Eldar, Yonina C
Convex Optimization in Signal Processing and Communications
Herausgeber: Palomar, Daniel P; Eldar, Yonina C
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Leading experts provide the theoretical underpinnings of the subject and tutorials on a wide variety of key applications.
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Leading experts provide the theoretical underpinnings of the subject and tutorials on a wide variety of key applications.
Produktdetails
- Produktdetails
- Verlag: Cambridge University Press
- Seitenzahl: 512
- Erscheinungstermin: 25. Januar 2010
- Englisch
- Abmessung: 257mm x 180mm x 20mm
- Gewicht: 930g
- ISBN-13: 9780521762229
- ISBN-10: 0521762227
- Artikelnr.: 28111773
- Verlag: Cambridge University Press
- Seitenzahl: 512
- Erscheinungstermin: 25. Januar 2010
- Englisch
- Abmessung: 257mm x 180mm x 20mm
- Gewicht: 930g
- ISBN-13: 9780521762229
- ISBN-10: 0521762227
- Artikelnr.: 28111773
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 of homogeneous 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. Rübsamen, 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. Palomar and
S. Barbarossa; 12. Nash equilibria: the variational approach F. Facchinei
and J. S. Pang.
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 of homogeneous 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. Rübsamen, 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. Palomar and
S. Barbarossa; 12. Nash equilibria: the variational approach F. Facchinei
and J. S. Pang.
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 of homogeneous 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. Rübsamen, 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. Palomar and
S. Barbarossa; 12. Nash equilibria: the variational approach F. Facchinei
and J. S. Pang.
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 of homogeneous 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. Rübsamen, 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. Palomar and
S. Barbarossa; 12. Nash equilibria: the variational approach F. Facchinei
and J. S. Pang.