Weber Problem Solver Generalization of Weiszfeld Algorithm in MATLAB

Total variation regularized least squares deconvolution is one of the standard problems in image processing. This package uses the concept of Augmented Lagrangian [1] to implement the state-of-the-art algorithm, which can be viewed as a variant of the widely known Alternating Direction Method of Multipliers (ADMM). The deconvtv user interface is similar to the current MATLAB deconvolution tools, including deconvwnr, deconvlucy, and deconvreg: out = deconvtv(img, psf, mu, opt); deconvtv supports direct spatiotemporal processing for image and video deconvolution problems. Its applications include, but are not limited to: image and video deblurring, image and video denoising, depth data enhancement, thermal air turbulence stabilization, and multi-view synthesis. For more information and citations, please refer to: [1] SH Chan, R. Khoshabeh, KB Gibson, PE Gill, and TQ Nguyen, \"Augmented Lagrangian Method for Total Variation Video Restoration\", IEEE Trans. Image.

固定起点/终点多旅行推销员问题 (M-TSP) 通过遗传算法 (GA) 解决 MTSPF_GA 是一个用于解决 固定多重旅行商问题（M-TSP）的 遗传算法（GA），其目的是通过GA搜索找到接近最优解的最短路线。每位推销员都从起点出发，经过一组独特的城市，最终返回起点。 主要特点： 每个推销员从第一个点出发，到第一个点结束，但旅行到中间的一组独特城市。 除了第一个城市，其他每个城市仅被一位推销员访问。 注意： 固定起点/终点位置被视为第一个XY点。 输入参数： XY（float）：一个Nx2的城市位置矩阵，其中N为城市数量。 DMAT（float）：城市间距离或成本的NxN矩阵。 NSALESMEN（标量整数）：访问城市的推销员数量。 MINTOUR（标量整数）：任何推销员的最小游览长度，不包括起点/终点。 POPSIZE（标量整数）：种群大小。

遗传算法是为无法通过称为NP-Hard问题的标准方法解决的问题找到足够好的解决方案的方法。虽然它不能保证最好的解决方案，但我们可以在该方法中为大多数工程问题找到相对足够好的解决方案[1]。高中大学等教育机构使用每周课程时间表以最佳方式使用所有资源。制定最佳每周时间表就是NP-Hard问题的一个例子，它无法用任何检查每个概率的粗暴方法解决。在这个存储库中，我们使用遗传算法提供了该问题的解决方案，该算法试图最小化确定的适应度函数，该函数是对时间表如何优化的一种度量[2]。

The Conservative Value Method MATLAB code Distribution_Planning_Lot_sizing_Decomposition.m is used for the Lagrangian Relaxation Method and decomposition algorithms applied to high-speed railway (CSHR) catering services. These programs are coded based on the following works: the time-varying demand and pedestrian congestion-based high-speed railway catering distribution planning problem and the batch-based model and decomposition algorithm developed by the Beijing Jiaotong University Research Team under the guidance of Professor Nie Lei. All these codes were written by Dr. Wu Xin. For any inquiries, please contact him. Your feedback is important to us, and the code will continue to be updated and improved in the future. The code includes three main parts: Main Program: main.m is the key component that initiates all related algorithms. The CPLEX solver used in the file can decompose the mixed-integer programming model into submodels. Therefore, the program will work only if the CPLEX interface is correctly installed in the MATLAB environment. Convex Program: A program that solves a series of single-variable convex maximization submodels. The submodels can be solved using the fmincon function in MATLAB's optimization toolbox. HCEA Functions: All files prefixed with HCEA_ embed the Convex Group Method (Frank Wolfe algorithm) as part of the Hybrid Cross-Entropy Algorithm (HCEA). The implementation of HCEA can be used to compare with the proposed decomposition method. Default settings are provided for various configurations.

PM_Solver_Matlab is an FEM solver developed using MATLAB for synchronous motors, with a focus on surface-mounted permanent magnet motors. Some of the code is based on or modified from Smeklib().

在本示例中，Matlab代码实现了非线性求解器，用于模拟多Kong介质中的流动。代码使用牛顿-拉夫森法求解方程f(x) = 0，基本步骤如下： 初始化x0。 计算更新：x1 = x0 - f(x0) / f'(x0)。 构建矩阵形式：A = df1/dx1 ... dfN/dxN，b = -f1 ... -fN。 解线性方程Ax = b，更新x = x + alpha * dx（对于非阻尼情况，alpha = 1）。 计算残差|f + f'dx| / |f|，检查收敛性。

Simulink仿真工具中，Solver选项卡扮演着关键角色。它包含Simulink time用于设置仿真的起始时间和停止时间，以及Solver options用于选择仿真解题器的操作。根据类型的不同，Solver options分为Variable-step（变步长算法）和Fixed-step（固定步长算法），应用于不同类型的仿真需求。

本项目建立PCA模型，使得PCA算子可以在任意时刻应用。实现基于MATLAB的PCA算法。

2011年秋季竞赛：藤蔓 该竞赛要求开发一个基于MATLAB的算法来模拟藤蔓的生长过程。藤蔓的生长规律需要在一定的约束条件下进行模拟，挑战在于如何高效地计算藤蔓的生长路径以及如何优化程序的执行效率。主要任务包括： 藤蔓的拓扑结构建模，模拟其在空间中的生长过程。 计算藤蔓生长过程中碰撞检测和环境交互。 使用MATLAB开发高效的模拟代码，保证算法的运行速度和准确性。 该项目涉及算法设计、数学建模和程序优化，考察了参赛者在MATLAB开发上的能力。