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Description: 半定规划，属于凸优化的一种，matlab 实现的源码，适合学习
Semidefinite Programming
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Size: 5046637 |
Author: 罗彤 |
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Description: GloptiPoly 3: moments, optimization and
semidefinite programming.
Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem of
Moments (GPM), an infinite-dimensional optimization problem which can be viewed as
an extension of the classical problem of moments [8]. From a theoretical viewpoint, the
GPM has developments and impact in various areas of mathematics such as algebra,
Fourier analysis, functional analysis, operator theory, probability and statistics, to cite
a few. In addition, and despite a rather simple and short formulation, the GPM has a
large number of important applications in various fields such as optimization, probability,
finance, control, signal processing, chemistry, cristallography, tomography, etc. For an
account of various methodologies as well as some of potential applications, the interested
reader is referred to [1, 2] and the nice collection of papers [5].
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Size: 200592 |
Author: askool |
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Description: 半定规划，属于凸优化的一种，matlab 实现的源码，适合学习
Semidefinite Programming-Semidefinite programming, belonging to a convex optimization, matlab source realization, suitable for study Semidefinite Programming
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Size: 5046272 |
Author: 罗彤 |
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Description: GloptiPoly 3: moments, optimization and
semidefinite programming.
Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem of
Moments (GPM), an infinite-dimensional optimization problem which can be viewed as
an extension of the classical problem of moments [8]. From a theoretical viewpoint, the
GPM has developments and impact in various areas of mathematics such as algebra,
Fourier analysis, functional analysis, operator theory, probability and statistics, to cite
a few. In addition, and despite a rather simple and short formulation, the GPM has a
large number of important applications in various fields such as optimization, probability,
finance, control, signal processing, chemistry, cristallography, tomography, etc. For an
account of various methodologies as well as some of potential applications, the interested
reader is referred to [1, 2] and the nice collection of papers [5].-GloptiPoly 3: moments, optimization andsemidefinite programming.Gloptipoly 3 is intended to solve, or at least approximate, the Generalized Problem ofMoments (GPM), an infinite-dimensional optimization problem which can be viewed asan extension of the classical problem of moments [8] . From a theoretical viewpoint, theGPM has developments and impact in various areas of mathematics such as algebra, Fourier analysis, functional analysis, operator theory, probability and statistics, to citea few. In addition, and despite a rather simple and short formulation, the GPM has alarge number of important applications in various fields such as optimization, probability, finance, control, signal processing, chemistry, cristallography, tomography, etc. For anaccount of various methodologies as well as some of potential applications, the interestedreader is referred to [ 1, 2] and the nice collection of papers [5].
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Size: 200704 |
Author: askool |
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Description: 著名的Sparco工具包。是matlab下解决线性约束，二阶锥约束和半定约束等优化问题的常用工具。-Sparco famous Kit. Are resolved under matlab linear constraints, second-order cone constraint and semidefinite constrained optimization problems, such as commonly used instrument.
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Size: 3881984 |
Author: Ma hua |
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Description: On the implementation and usage of SDPT3
– a Matlab software package for
semidefinite-quadratic-linear programming,
version 4.0
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Author: hnytsyz |
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Description: Optimization method, convex programming, semidefinite programming, nonlinear optimization
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Author: Harry |
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Description: Semidefinite programming, LIEVEN VANDENBERGHE AND STEPHEN BOYD
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Size: 4988928 |
Author: iutboy |
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Description: 一个求解半正定规划的数值算法包，包括 C 语言实现的源代码和 MATLAB 的调用接口。这是目前项目发布的最新版本 6.1.0。-Copyright 1997-2010, Brian Borchers. This copy of CSDP is made
available under the Common Public License. See LICENSE for the
details of the CPL.
CSDP is a software package for solving semidefinite programming
problems. The algorithm is a predictor-corrector version of the
primal-dual barrier method of Helmberg, Rendl, Vanderbei, and
Wolkowicz.
This file includes binary code for SDP for Windows.
doc documentation.
matlab MATLAB/Octave routines for interfacing to CSDP.
bin The binary code.
Contact/Support:
If you are having trouble running the code, see the doc directory
first. The project s website can be found at
https://projects.coin-or.org/Csdp/
The project s maintainer can be reached by email at borchers@nmt.edu. Please
email bug reports and feature requests.
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Author: bsmyht |
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Description: SeDuMi 是一个求解半正定规划的算法包，这是项目最新发布的源代码。-Welcome to SeDuMi 1.3
SeDuMi is a Matlab Toolbox for Linear, Second order, Semidefinite or mixed
problems. It can handle free variables and complex data as well.
To obtain the latest version of SeDuMi, see
http://sedumi.ie.lehigh.edu
Installation instructions can be found in the file
Install.txt
After you installed the binaries please type
help sedumi
in Matlab to get more information. Example problems can be found
in the folder /examples, documentation is in /doc.
For a list of changes check the file Changelog.txt.
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Author: bsmsht |
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Description: semidefinite programming
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Author: param |
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Description: 几种 MIMO 最大似然检测算法性能与复杂度比较及改进，介绍了半定松弛、分枝定界和堆栈三种低复杂度最大似然检测算法，并对其性能和复杂度进行了仿真分析，提出了改进的分枝定界和堆栈算法，仿真结果证明分枝定界和堆栈算法性能要优于半定松弛算法，分枝定界算法的复杂度低于堆栈算法且半定松弛算法以多项式复杂度取得了逼近最大似然的性能，同时改进算法加快了算法收敛速度，降低了计算复杂度和对存储空间的要求。
-Several maximum likelihood MIMO detection algorithm performance and complexity comparison and improvement, introduced the semidefinite relaxation, branch and bound, and the stack of three low-complexity maximum likelihood detection algorithm and its performance and complexity of the simulation analysis , proposed an improved branch and bound, and the stack algorithm, simulation results show that the stack algorithm branch and bound and given a better performance than a half relaxation algorithm, branch and bound algorithm complexity is lower than the stack algorithm and the algorithm for semidefinite relaxation polynomial complexity approximation of the maximum likelihood achieved performance, while improving the algorithm to speed up the convergence rate and reduces the computational complexity and storage space requirements.
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Author: wanglong |
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Description: 解log-det半定规划的matlab软件包，对解优化问题很有用。-A MATLAB software package for log-determinant semidefinite programming, it is useful to solve optimization problems.
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Size: 219136 |
Author: yishuiwang |
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Description: 基于MATLAB内点算法求解SDP半正定规划软件包-MATLAB-based interior-point algorithm for solving semidefinite program package SDP
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Size: 131072 |
Author: 张均 |
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Description: Semidefinite Relaxation for Downlink OFDMA
Resource Allocation Using Adaptive Modulation uploaded by J.Yashashchandra (jyashashchandra@yahoo.com)
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Size: 161792 |
Author: Ashiwinilade |
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Description: 求解半定规划的工具包，很多地方都需要用到，很有用-Solving semidefinite programming toolkit, many places are needed, useful
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Author: 刘文俊 |
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Description: Estimate sensor positions based on semidefinite programming relaxation of the non-convex optimization problem (1), followed by steepest descent with backtracking line search on smooth unconstrained problem (2).
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Author: uwsn |
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Description: The papers are special sections about the applications of convex optimization in signal processing, and they are especially related to physical layer security and beamforming. As a mathmatical tool, convex optimization can help resolve weight design issues subject to certain constraints in beamforming. The semidefinite relaxation technique is of great importance to convert a non-convex problem to a convex one.
The papers included are:
1.Convex optimization based beamforming
2.Convex optimization in signal processing from the guest editors
3.Dynamic resource allocation in cognitive radio networks
4.Real-time convex optimization in signal processing
5.Semidifinite relaxation of quadratic optimization problems
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Author: spicioussky |
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Description: Semidefinite Programming Approaches for Sensor Network Localization With Noisy Distance Measurements
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Size: 787456 |
Author: M.Hasani |
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Description: 现有的向量加权稳健波束形成方法只有在指向误差较小的情况下才能有效估计目标的信号功率；矩阵加权波束形成方法在指向误差较大时，虽然可以估计目标的信号功率，但是它的系统实现复杂度与向量加权稳健波束形
成方法相比较大。针对以上问题，该文提出基于半正定秩松弛(SDR)方法的稳健波束形成，该方法优化模型中的目标函数与Capon 算法的目标函数相同，优化变量为加权向量的协方差矩阵，并约束方向图的主瓣幅度波动范围、旁瓣电平，协方差矩阵的秩为1。-The existing vector weighted robust beamforming is able to estimate the signal power of target only in
situations of a small steering angle error. For a larger steering angle error case, although the matrix weighted
beamforming can effectively estimate the signal power of the target as well, the system implementation is more
complicated than above mentioned vector weighted. In order to solve these problems, this paper presents a new
robust beamforming approach based on SemiDefinite rank Relaxation (SDR). Detailed description of the proposed
method are given as follows: the optimal model has the same objective as that of the Capon algorithm the
optimization variable is the covariance matrix of weight vector with constraints posed on the ripple of mainlobe
amplitude and sidelobe level, and the rank of covariance matrix is 1.
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Size: 688128 |
Author: treedev |
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