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检索条件"主题词=quadratic semidefinite programming"
14 条 记 录,以下是1-10 订阅
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quadratic semidefinite programming for Waveform-Constrained Joint Filter-Signal Design in STAP
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IEEE TRANSACTIONS ON SIGNAL PROCESSING 2020年 68卷 1744-1759页
作者: O'Rourke, Sean M. Setlur, Pawan Rangaswamy, Muralidhar Swindlehurst, A. Lee Univ Calif Irvine Irvine CA 92697 USA US Air Force Res Lab Wright Patterson AFB OH 45433 USA Riverside Res Dayton OH 45431 USA
In waveform-adaptive space-time adaptive processing (STAP), signal-dependent interference can be mitigated through joint filter-signal design. For the common signal-to-interference-plus-noise ratio (SINR) optimality c... 详细信息
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Modified alternating direction method of multipliers for convex quadratic semidefinite programming
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NEUROCOMPUTING 2016年 214卷 575-586页
作者: Chang, Xiaokai Liu, Sanyang Li, Xu Xidian Univ Sch Math & Stat Xian 710071 Peoples R China Lanzhou Univ Technol Coll Sci Lanzhou 730050 Peoples R China
The direct extension of alternating direction method of multipliers (ADMM) is not necessarily convergent to the dual form of convex quadratic semidefinite programming (CQSDP) problems, though the convergence of ADMM i... 详细信息
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QSDPNAL: a two-phase augmented Lagrangian method for convex quadratic semidefinite programming
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MATHEMATICAL programming COMPUTATION 2018年 第4期10卷 703-743页
作者: Li, Xudong Sun, Defeng Toh, Kim-Chuan Princeton Univ Dept Operat Res & Financial Engn Sherrerd Hall Princeton NJ 08544 USA Hong Kong Polytech Univ Dept Appl Math Hong Kong Hong Kong Peoples R China Natl Univ Singapore Dept Math 10 Lower Kent Ridge Rd Singapore 119076 Singapore Natl Univ Singapore Inst Operat Res & Analyt 10 Lower Kent Ridge Rd Singapore 119076 Singapore
In this paper, we present a two-phase augmented Lagrangian method, called QSDPNAL, for solving convex quadratic semidefinite programming (QSDP) problems with constraints consisting of a large number of linear equality... 详细信息
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A sensitivity result for quadratic semidefinite programs with an application to a sequential quadratic semidefinite programming algorithm
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COMPUTATIONAL & APPLIED MATHEMATICS 2012年 第1期31卷 205-218页
作者: Garces, Rodrigo Gomez, Walter Jarre, Florian Univ La Frontera Dept Engn Math Temuco 01145 Chile EuroAmerica SA Santiago Chile Univ Dusseldorf Inst Math D-40225 Dusseldorf Germany
In this short note a sensitivity result for quadratic semidefinite programming is presented under a weak form of second order sufficient condition. Based on this result, also the local convergence of a sequential quad... 详细信息
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Alternating direction method for bi-quadratic programming
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JOURNAL OF GLOBAL OPTIMIZATION 2011年 第3期51卷 429-446页
作者: Hu, Sheng-Long Huang, Zheng-Hai Tianjin Univ Sch Sci Dept Math Tianjin 300072 Peoples R China
Bi-quadratic programming (Bi-QP for short) was studied systematically in Ling et al. (SIAM J. Optim. 20:1286-1320, 2009) due to its various applications in engineering as well as optimization. Several approximation me... 详细信息
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Convergent prediction-correction-based ADMM for multi-block separable convex programming
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JOURNAL OF COMPUTATIONAL AND APPLIED MATHEMATICS 2018年 335卷 270-288页
作者: Chang, Xiaokai Liu, Sanyang Zhao, Pengjun Li, Xu Xidian Univ Sch Math & Stat Xian 710071 Shaanxi Peoples R China Lanzhou Univ Technol Coll Sci Lanzhou 730050 Gansu Peoples R China Shanglue Univ Sch Math & Comp Applicat Shanglue 726000 Peoples R China
The direct extension of the classic alternating direction method with multipliers (ADMMe) to the multi-block separable convex optimization problem is not necessarily convergent, though it often performs very well in p... 详细信息
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A SEQUENTIAL SEMISMOOTH NEWTON METHOD FOR THE NEAREST LOW-RANK CORRELATION MATRIX PROBLEM
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SIAM JOURNAL ON OPTIMIZATION 2011年 第4期21卷 1641-1666页
作者: Li, Qingna Qi, Hou-Duo Hunan Univ Coll Math & Econometr Changsha 410082 Hunan Peoples R China Univ Southampton Sch Math Southampton SO17 1BJ Hants England
Based on the well-known result that the sum of the largest eigenvalues of a symmetric matrix can be represented as a semidefinite programming problem (SDP), we formulate the nearest low-rank correlation matrix problem... 详细信息
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A primal majorized semismooth Newton-CG augmented Lagrangian method for large-scale linearly constrained convex programming
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COMPUTATIONAL OPTIMIZATION AND APPLICATIONS 2017年 第3期68卷 503-532页
作者: Wang, Chengjing Tang, Peipei Southwest Jiaotong Univ Sch Math 999 Xian RdWest PkHightech Zone Chengdu 611756 Sichuan Peoples R China Zhejiang Univ City Coll Sch Comp Sci Hangzhou 310015 Zhejiang Peoples R China
In this paper, we propose a primal majorized semismooth Newton-CG augmented Lagrangian method for large-scale linearly constrained convex programming problems, especially for some difficult problems. The basic idea of... 详细信息
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A projected semismooth Newton method for problems of calibrating least squares covariance matrix
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OPERATIONS RESEARCH LETTERS 2011年 第2期39卷 103-108页
作者: Li, Qingna Li, Donghui S China Normal Univ Sch Math Sci Guangzhou 510631 Guangdong Peoples R China Chinese Acad Sci Inst Computat Math & Sci Engn Comp Beijing 100080 Peoples R China
In this paper we propose a projected semismooth Newton method to solve the problem of calibrating least squares covariance matrix with equality and inequality constraints. The method is globally and quadratically conv... 详细信息
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A lower bound for the nearest correlation matrix problem based on the circulant mean
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COMPUTATIONAL & APPLIED MATHEMATICS 2014年 第1期33卷 27-44页
作者: Travaglia, M. V. Univ Fed Piaui Ctr Ciencias Nat Dept Matemat BR-64049550 Teresina PI Brazil
This paper deals with the problem of finding the nearest correlation matrix to a given n x n symmetric matrix . We say that is a correlation matrix if it is symmetric positive semidefinite whose diagonal entries are e... 详细信息
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