搜索结果: 1-12 共查到“数学 semidefinite programming”相关记录12条 . 查询时间(0.098 秒)
Academy of Mathematics and Systems Science, CAS Colloquia & Seminars:A Squared Smoothing Newton Method for Semidefinite Programming
半定规划 平方平滑 牛顿方法
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2023/4/14
Optimal excitation signal design for frequency domain system identification using semidefinite programming
The optimal excitation signal and the dispersion function semidefinite programming linear matrix inequality (lmi)
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2015/8/11
The paper discusses two methods of optimal excitation signal design for identification with Maximum Likelihood parameter estimation: The ‘classical’, dispersion function based method, and a new, semid...
Semidefinite programming
Semidefinite programming linear function affine combination symmetric positive semidefinite matrix nonlinear not smooth
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2015/8/11
In semidefinite programming we minimize a linear function subject to the constraint that an affine combination of symmetric matrices is positive semidefinite. Such a constraint is nonlinear and nonsmo...
Semidefinite programming relaxations of non-convex problems in control and combinatorial optimization
Applications of semidefinite programming combinatorial optimization quadratic semi-definite programming bilinear matrix inequality
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2015/8/11
We point out some connections between applications of semidefinite programming in control and in combinatorial optimization. In both fields semidefinite programs arise as convex relaxations of NP-hard...
Designing fast distributed iterations via semidefinite programming
Iteration markov chain the transition probability mixing ratio the monte carlo markov chain
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2015/8/11
The general setting we consider involves a process, iteration, or method in which the computation or communication at each step is local, determined by a given graph, and involves some parameters or c...
Generalized Chebyshev bounds via semidefinite programming
Quadratic inequality convex optimization computation single variable and random variable chebyshev inequality
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2015/8/10
A sharp lower bound on the probability of a set defined by quadratic inequalities, given the first two moments of the distribution, can be efficiently computed using convex optimization. This result g...
A semidefinite programming method for integer convex quadratic minimization
The quadratic function the probability of integer zinc, values
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2015/8/7
We consider the NP-hard problem of minimizing a convex quadratic function over the integer lattice Zn. We present a semidefinite programming (SDP) method for obtaining a nontrivial lower bound on the ...
Semidefinite Programming Relaxations and Algebraic Optimization in Control
Control Algebraic Optimization
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2015/6/19
We present an overview of the essential elements of semidefinite programming as a computational tool for the analysis of systems and control problems. We make particular emphasis on general duality pr...
A Stochastic Smoothing Algorithm for Semidefinite Programming
Semidefinite programming Gaussian smoothing eigenvalue problems
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2012/4/18
We use a rank one Gaussian perturbation to derive a smooth stochastic approximation of the maximum eigenvalue function. We then combine this smoothing result with an optimal smooth stochastic optimiza...
Linear Index Coding via Semidefinite Programming
Linear Index Coding Semidefinite Programming Data Structures and Algorithms
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2011/9/30
Abstract: In the index coding problem, introduced by Birk and Kol (INFOCOM, 1998), the goal is to broadcast an n bit word to n receivers (one bit per receiver), where the receivers have side informati...
Optimal and Robust Transmit Designs for MISO Channel Secrecy by Semidefinite Programming
Optimal Robust Transmit Designs for MISO Channel Secrecy Semidefinite Programming
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2011/2/22
In recent years there has been growing interest in study of multi-antenna transmit designs for
providing secure communication over the physical layer. This paper considers the scenario of an intended...
Applications of semidefinite programming to coding theory
Applications semidefinite programming to coding theory
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2010/12/1
We survey recent generalizations and improvements of the linear programming method that involve semidefinite programming. A general framework using group representations and tools from graph theory is...