Description: 通过对经典的lemke互补转轴算法求解含有等式约束的凸二次规划问题的分析，发现所得到的线性互补问题(lcp)可能是退化的．由lemke算法求解(lcp)问题的迭代过程，通过六个命题说明了含有等式约束的凸二次规划问题对应的(lcp)问题退化的原因，并对经典的lemke算法的迭代过程进行修正，提出了一种改进的lemke算法，这种算法能有效地搜索到含等式约束凸二次规划问题的最优解．-Through the classic Lemke complementarity algorithm shaft containing the convex equality constrained quadratic programming problem of the analysis, we found by the linear complementarity problem (lcp) may be degraded. Algorithm by Lemke (lcp) of the iterative process of questions, through the six propositions that contain equality constraints of convex quadratic programming problem corresponding to (lcp) questions the reasons for degradation of the classic Lemke algorithm iterative process amendments put forward an improved Lemke algorithm can effectively containing english convex equality constrained quadratic programming problem of the optimal solution. Platform: |
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Author:王旭 |
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Description: 当前论文主要考虑的是非信号依赖的高斯噪声下的图像恢复，本程序实现了泊松噪声下的图像恢复，泊松噪声为信号依赖噪声，能够更加有效逼近实际成像系统噪声。- This is the code that was used in the papers "A Nonnnegatively Constrained Convex Programming Method for Image Reconstruction", "Total Variation-Penalized Poisson Likelihood Estimation for Ill-Posed Problems", "Tikhonov Regularized Poisson Likelihood Estimation: Theoretical Justification and a Computational Method", "An Efficient Computational Method for Total Variation with Poisson Negative-Log Likelihood", "An Analysis of Regularization by Diffusion for Ill-Posed Poisson Likelihood Estimation," "An Iterative Method for Edge-Preserving MAP Estimation when Data-Noise is Poisson", and finally, "Regularization Parameter Selection Methods for Ill-Posed Poisson Maximum Likelihood Estimation". See my publications page for more details. The main algorithm is for nonnegatively constrained, regularized Poisson likelihood estimation. At this point you can choose Tikhonov, total variation regularization, and diffusion regularization. A number of other methods are also implemented. Regularizatio Platform: |
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Author:sun |
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Description: SVM方法的基本思想是：定义最优线性超平面，并把寻找最优线性超平面的算法归结为求解一个凸规划问题。进而基于Mercer核展开定理，通过非线性映射φ，把样本空间映射到一个高维乃至于无穷维的特征空间（Hilbert空间），使在特征空间中可以应用线性学习机的方法解决样本空间中的高度非线性分类和回归等问题。svm 程序，即支持向量机的代码。-The basic idea of SVM method are: the definition of the optimal linear hyperplane, and the search algorithm for optimal linear hyperplane by solving a convex programming problem. Then based on Mercer nuclear expansion theorem, through a nonlinear mapping φ, the sample space is mapped to a high-dimensional and even infinite dimensional feature space (Hilbert space), so that in the feature space can be applied to solve the linear learning machine method, the sample space The highly nonlinear classification and regression problems. svm procedures that support vector machine code. Platform: |
Size: 117760 |
Author:秀 |
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Description: Matlab编程考试的一道题。随机生成50个点，计算它的一个凸包，并计算凸包的面积-Matlab programming test a question. Randomly generated 50 points, calculate a convex hull, and calculate the area of ??convex hull Platform: |
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Author:陶兆君 |
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Description: convex programming
CVX is a Matlab-based modeling system for convex optimization. CVX turns Matlab into a modeling language, allowing constraints and objectives to be specified using standard Matlab expression syntax. Platform: |
Size: 17783808 |
Author:rahele |
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Description: 使用内点法，解决凸优化问题，此方法(Interior Point Method)是一种求解线性规划或非线性凸优化问题的算法。(The interior point method is used to solve the convex optimization problem. This method (Interior, Point, Method) is an algorithm for solving linear programming or nonlinear convex optimization problems.) Platform: |
Size: 13312 |
Author:Aaron1991
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