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4mult
- 可用的4位乘法器，用VHDL在FPGA中实现-available four multipliers, FPGA VHDL in achieving
hyplas
- ************************************************************************ * * * * * THIS IS THE H Y P L A S 2.0 README FILE * * ----------------- * * * * HYPLAS is a finite element program for implicit small and large * * strain analisys of hyperelast
exact_alm_rpca
- RPCA (Robust Principal Component Analysis)是目前用于矩阵填充、图像去噪的最有效的优化方法。该代码是求解RPCA的一种数值算法——Exact ALM（Exact Augmented Lagrange Multiplier）-The most basic form of the exact ALM function is [A, E] = exact_alm_rpca(D, λ), and that of the inexact ALM function i
zuiyouhuashiyanbaogao
- 用MATLAB求解无约束的问题，主要有最速下降法，牛顿法，共轭梯度法，变尺度法（DFP和BFGS法），非线性最小二乘法。 用MATLAB求解有约束的问题，主要是外惩罚函数和广义乘子法。 以及一些对具体问题的分析，MATLAB的代码在文档里都有。 -Using MATLAB to solve the problem of non-binding, there are the steepest descent method, Newton method, conjugate gradie
optimizatiom-ariszheng2005
- 关于最大最小值，用拉格朗日乘子算法来解决。-Minimum value on the largest, with Lagrange multipliers to solve the algorithm.
titanium
- VC Support Vector Classification Usage: [nsv alpha bias] = svc(X,Y,ker,C) Parameters: X - Training inputs Y - Training targets ker - kernel function C - upper bound (non-separable case) nsv - number of support vectors alpha -
chengzifa
- 基本的拉格朗日乘子法(又称为拉格朗日乘数法)，就是求函数f(x1,x2,...)在g(x1,x2,...)=0的约束条件下的极值的方法。其主要思想是引入一个新的参数λ（即拉格朗日乘子），将约束条件函数与原函数联系到一起，使能配成与变量数量相等的等式方程，从而求出得到原函数极值的各个变量的解。 -Basic Lagrange multipliers (also known as Lagrange multiplier method), is of a function f (x1, x2 ,.
MATLAB
- MATLAB函数参考手册，查看matlab函数作用以及功能。- SVMLSPex02.m Two Dimension SVM Problem, Two Class and Separable Situation Difference with SVMLSPex01.m: Take the Largrange Function (16)as object function insteads ||W||, so it need more
Fisherfenleiqi
- 理解Fisher准则方法确定最佳线性分界面方法的原理，以及拉格朗日乘子求解的原理-Fisher criterion to determine the best way to understand the interface methods of linear theory, and the principle of Lagrange multipliers to solve
LADM_LRR
- This the alternating direction method of multipliers by Zouchen Lin-This is the alternating direction method of multipliers by Zouchen Lin
Onestep
- This the one step alternating direction method of multipliers by Deren Han-This is the one step alternating direction method of multipliers by Deren Han
newton_lagrange
- 在matlab r2010a环境下编写的newton-lagrange算法，可以求解约束优化问题，程序返回目标函数值及拉格朗日乘子。-In matlab r2010a environment prepared newton-lagrange algorithms can solve constrained optimization problems, the program returns the value of the objective function and Lagrange mult
Lagrange-multipliers
- 在matlab的环境下实现拉格朗日乘子法 -matlab achieve Lagrange multipliers
ADMM
- The alternating direction method of multipliers优化算法。简称ADMM，是机器学习中比较广泛使用的约束问题最优化方法。-The alternating direction method of multipliers optimization algorithm. Acronym ADMM, the machine learning problem is more widespread use of constraint optimization me
Solver_Cosparse_ADMM
- Solver of Alternating Direction Method of Multipliers for analysis model
Huber
- 机器学习ADMM Huber损失最小化1范式约束算法Sparse Huber With L1 Constrain And Alternating Direction Method of Multipliers Method-Sparse Huber With L1 Constrain And Alternating Direction Method of Multipliers Method
ADMM_ALL
- 张量分解在推荐系统中有重要作用，代码实现张量的CP分解,用ADMM算法实现(We design an algorithm based on the Alternating Direction Method of Multipliers (ADM- M) technique. Experiments on real-world datasets find that the proposed model outperforms traditional methods.)
Deep-ADMM-Net-master
- Net is defined over a data flow graph, which is derived from the iterative pro- cedures in Alternating Direction Method of Multipliers (ADMM) algorithm for optimizing a CS-based MRI model. In the training phase, all parameters of the net, e.g., im
admm_lin_inv
- ADMM 交替方向乘子法Alternating Direction Method of Multipliers(Alternating Direction Method of Multipliers)
FELICITY
- There are many finite element packages available, both commercial and free. FELICITY is designed for simulating problems where sub-domains interact in non-trivial ways, i.e. Partial Differential Equations (PDEs) on surfaces (e.g. Laplace-Beltrami) in