国外信息科学与技术优秀图书系列·电子学与通信技术:信号处理与通信中的凸优化理论(英文版)

目 录内容简介
List of contributor
Preface
1 Automatic code generation for real.time convex optimization
Jacob Mattingley and Stephen Boyd
1.1 Introduction
1.2 Solver and specification languages
1.3 Examples
1.4 Algorithm corideratior
1.5 Code generation
1.6 CVXMOD:a preliminary implementation
1.7 Numerical examples
1.8 Summary,conclusior,and implicatior
Acknowledgments
References
2 Gradient-based algorithms with applicatior to signal-recovery problems
Arnir Beck and Marc Teboulle
2.1 Introduction
2.2 The general optimization model
2.3 Building gradient-based schemes
2.4 Convergence results tor the proximal-gradient method
2.5 A fast proximal-gradient method
2.6 Algorithms for It-based regularization problems
2.7 TV-based restoration problems
2.8 The source-localization problem
2.9 Bibliographic notes
References
3 Graphical models of autoregressive processes
Jitkomut Songsiri,Joachim Dahl,and Lieven Vandenberghe
3.1 Introduction
3.2 Autoregressive processes
3.3 Autoregressive graphical models
3.4 Numerical examples
3.5 Conclusion
Acknowledgments
References
4 SDP relaxation of homogeneous quadratic optimization:approximation bounds and applicatior Zhi-Quan Luo and Tsung-Hui Chang
4.1 Introduction
4.2 Nonconvex QCQPs and SDP relaxation
4.3 SDP relaxation for separable homogeneous QCQPs
4.4 SDP relaxation for maximization homogeneous QCQPs
4.5 SDP relaxation for fractional QCQPs
4.6 More applicatior of SDP relaxation
4.7 Summary and discussion
Acknowledgments
References
5 ProbabilisUc analysis of semidefinite relaxation detector for multiple-input,multiple-output systems
Anthony Man-Cho So and Yinyu Ye
5.1 Introduction
5.2 Problem formulation
5.3 Analysis of the SDR detector for the MPSK cortellatior
5.4 Exterion to the QAM cortellatior
5.5 Concluding remarks
Acknowledgments
References
6 Semidefinite programming,matrix decomposition,and radar code design
Yongwei Huang,Antonio De Maio,and Shuzhong Zhang
6.1 Introduction and notation
6.2 Matrix rank- 1 decomposition
6.3 Semidefinite programming
6.4 Quadratically cortrained quadratic programming and its SDP relaxation
6.5 Polynomially solvable QCQP problems
6.6 The radar code-design problem
6.7 Performance measures for code design
6.8 Optimal code design
6.9 Performance analysis
6.10 Conclusior
References
7 Convex analysis for non-negative blind source separation with application in imaging
Wing-Kin Ma,Tsung-Han Chan,Chong-Yung Chi,and Yue Wang
7.1 Introduction
7.2 Problem statement
7.3 Review of some concepts in convex analysis
7.4 Non-negative,blind source-separation criterion via CAMNS
7.5 Systematic linear-programming method for CAMNS
7.6 Alternating volume-maximization heuristics for CAMNS
7.7 Numerical results
7.8 Summary and discussion
Acknowledgments
References
8 Optimization techniques in modern sampling theory
Tomer Michaeli and Yonina C.Eldar
8.1 Introduction
8.2 Notation and mathematical preliminaries
8.3 Sampling and recortruction setup
8.4 Optimization methods
8.5 Subspace prior
8.6 Smoothness prior
8.7 Comparison of the various scenarios
8.8 Sampling with noise
8.9 Conclusior
Acknowledgments
References
9 Robust broadband adaptive beamforming using convex optimization
Michael Riibsamen,Amr EI-Keyi,Alex B.Gerhman,and Thia Kirubarajan
9.1 Introduction
9.2 Background
9.3 Robust broadband beamformer
9.4 Simulatior
9.5 Conclusior
Acknowledgments
References
10 Cooperative distributed multi-agent optimization
Angelia Nedic and Asuman Ozdaglar
10.1 Introduction and motivation
10.2 Distributed-optimization methods using dual decomposition
10.3 Distributed-optimization methods using corerus algorithms
10.4 Exterior
10.5 Future work
10.6 Conclusior
10.7 Problems
References
11 Competitive optimization of cognitive radio MIMO systems via game theory
Gesualso Scutari,Daniel P.Palomar,and Sergio Barbarossa
11.1 Introduction and motivation
11.2 Strategic non-cooperative games:basic solution concepts and algorithms
11.3 Opportunistic communicatior over unlicered bands
11.4 Opportunistic communicatior under individual-interference cortraints
11.5 Opportunistic communicatior under global-interference cortraints
21.6 Conclusior
Acknowledgments
References
12 Nash equilibria:the variational approach
Francisco Facchinei and Jong-Shi Pang
12.1 Introduction
12.2 The Nash-equilibrium problem
12.3 Existence theory
12.4 Uniqueness theory
12.5 Seritivity analysis
12.6 Iterative algorithms
12.7 A communication game
Acknowledgments
References
Afierword
Index
Preface
1 Automatic code generation for real.time convex optimization
Jacob Mattingley and Stephen Boyd
1.1 Introduction
1.2 Solver and specification languages
1.3 Examples
1.4 Algorithm corideratior
1.5 Code generation
1.6 CVXMOD:a preliminary implementation
1.7 Numerical examples
1.8 Summary,conclusior,and implicatior
Acknowledgments
References
2 Gradient-based algorithms with applicatior to signal-recovery problems
Arnir Beck and Marc Teboulle
2.1 Introduction
2.2 The general optimization model
2.3 Building gradient-based schemes
2.4 Convergence results tor the proximal-gradient method
2.5 A fast proximal-gradient method
2.6 Algorithms for It-based regularization problems
2.7 TV-based restoration problems
2.8 The source-localization problem
2.9 Bibliographic notes
References
3 Graphical models of autoregressive processes
Jitkomut Songsiri,Joachim Dahl,and Lieven Vandenberghe
3.1 Introduction
3.2 Autoregressive processes
3.3 Autoregressive graphical models
3.4 Numerical examples
3.5 Conclusion
Acknowledgments
References
4 SDP relaxation of homogeneous quadratic optimization:approximation bounds and applicatior Zhi-Quan Luo and Tsung-Hui Chang
4.1 Introduction
4.2 Nonconvex QCQPs and SDP relaxation
4.3 SDP relaxation for separable homogeneous QCQPs
4.4 SDP relaxation for maximization homogeneous QCQPs
4.5 SDP relaxation for fractional QCQPs
4.6 More applicatior of SDP relaxation
4.7 Summary and discussion
Acknowledgments
References
5 ProbabilisUc analysis of semidefinite relaxation detector for multiple-input,multiple-output systems
Anthony Man-Cho So and Yinyu Ye
5.1 Introduction
5.2 Problem formulation
5.3 Analysis of the SDR detector for the MPSK cortellatior
5.4 Exterion to the QAM cortellatior
5.5 Concluding remarks
Acknowledgments
References
6 Semidefinite programming,matrix decomposition,and radar code design
Yongwei Huang,Antonio De Maio,and Shuzhong Zhang
6.1 Introduction and notation
6.2 Matrix rank- 1 decomposition
6.3 Semidefinite programming
6.4 Quadratically cortrained quadratic programming and its SDP relaxation
6.5 Polynomially solvable QCQP problems
6.6 The radar code-design problem
6.7 Performance measures for code design
6.8 Optimal code design
6.9 Performance analysis
6.10 Conclusior
References
7 Convex analysis for non-negative blind source separation with application in imaging
Wing-Kin Ma,Tsung-Han Chan,Chong-Yung Chi,and Yue Wang
7.1 Introduction
7.2 Problem statement
7.3 Review of some concepts in convex analysis
7.4 Non-negative,blind source-separation criterion via CAMNS
7.5 Systematic linear-programming method for CAMNS
7.6 Alternating volume-maximization heuristics for CAMNS
7.7 Numerical results
7.8 Summary and discussion
Acknowledgments
References
8 Optimization techniques in modern sampling theory
Tomer Michaeli and Yonina C.Eldar
8.1 Introduction
8.2 Notation and mathematical preliminaries
8.3 Sampling and recortruction setup
8.4 Optimization methods
8.5 Subspace prior
8.6 Smoothness prior
8.7 Comparison of the various scenarios
8.8 Sampling with noise
8.9 Conclusior
Acknowledgments
References
9 Robust broadband adaptive beamforming using convex optimization
Michael Riibsamen,Amr EI-Keyi,Alex B.Gerhman,and Thia Kirubarajan
9.1 Introduction
9.2 Background
9.3 Robust broadband beamformer
9.4 Simulatior
9.5 Conclusior
Acknowledgments
References
10 Cooperative distributed multi-agent optimization
Angelia Nedic and Asuman Ozdaglar
10.1 Introduction and motivation
10.2 Distributed-optimization methods using dual decomposition
10.3 Distributed-optimization methods using corerus algorithms
10.4 Exterior
10.5 Future work
10.6 Conclusior
10.7 Problems
References
11 Competitive optimization of cognitive radio MIMO systems via game theory
Gesualso Scutari,Daniel P.Palomar,and Sergio Barbarossa
11.1 Introduction and motivation
11.2 Strategic non-cooperative games:basic solution concepts and algorithms
11.3 Opportunistic communicatior over unlicered bands
11.4 Opportunistic communicatior under individual-interference cortraints
11.5 Opportunistic communicatior under global-interference cortraints
21.6 Conclusior
Acknowledgments
References
12 Nash equilibria:the variational approach
Francisco Facchinei and Jong-Shi Pang
12.1 Introduction
12.2 The Nash-equilibrium problem
12.3 Existence theory
12.4 Uniqueness theory
12.5 Seritivity analysis
12.6 Iterative algorithms
12.7 A communication game
Acknowledgments
References
Afierword
Index
目 录内容简介
凸优化理论是信号处理领域具有重要应用价值的理论分析工具,最近二 十年一大批的信号处理问题 都基于凸优化理论取得了突破进展。《国外信息科学与技术优秀图书系列·电子学与通信技术:信号处理与通信中的凸优化理论(英文版)》以通信与信号处理中的经典与前沿问题为脉络,深入浅出 地介 绍了各类凸优化分析的建模方法与基本理论。内容包括图模型理论、基于梯 度的信号重建算法、半定松弛(SDP)算法、基于SDP的雷达信号设计、图像处 理中的盲信源分离、现代抽样理论,特别是宽带移动 通信中的MIMO信号检测、认知无线电中的波束成形理论、分布式多目标优化 理论与博弈论等。本书可作为电子与通信工程等相关领域 科研人员、工程技术人员的参考书,也可供相关专业高年级 本科生、研究生阅读。
比价列表价格走势
公众号、微信群

微信公众号

实时获取购书优惠