Hough-circle-detection

小波变换的matlab源程序，有两个版本，这是第二板。(wavelet transform Matlab source, there are two versions, which is the second plate.)

RS 码译码源程序,在Visual c++下可对比4元域上的RS码进行纠错译码.(RS decoder source, in Visual c contrast under four yuan domain of RS error correction code for decoding.)

A boost converter is directly connected to the PV array with MPPT for operating at the maximum power point. A regulation cascades (current/voltage) applied using SMC for the control of DC converter a loop of voltage makes it possible to produce the current of reference.

对比各种小波变换的效果，B为输入的原始数据，需要自己添加数据并设置为B(Comparative effects of various wavelet transform, B is the input original data, and the data they need to be added to B)

matlab环境下的程序对数据进行标准化，此程序简单易懂，效率也非常高，是一个非常好的程序代码，非常值得推荐！(matlab environment, the data standardization process, this process easy to understand, efficiency is very high, is a very good code, very recommendable!)

Cholesky分解，以某个具体的矩阵进行的分解，便于求解线性方程组(Cholesky decomposition)

This package contains the code for the Enhanced Local Subspace Affinity (ELSA) with Enhanced Model Selection (EMS+) and number of motions estimation based on the eigenvalue spectrum of the Symmetric Normalized Laplacian matrix.

uma funcao que faz a simples deslocar vetor

采用栅格对机器人的工作空间进行划分，再利用优化算法对机器人路径优化，是采用智能算法求最优路径的一个经典问题。目前，采用蚁群算法在栅格地图上进行路径优化取得比较好的效果，而利用遗传算法在栅格地图上进行路径优化在算法显得更加难以实现。 利用遗传算法处理栅格地图的机器人路径规划的难点主要包括：1保证路径不间断，2保证路径不穿过障碍。 用遗传算法解决优化问题时的步骤是固定的，就是种群初始化，选择，交叉，变异，适应度计算这样，那么下面我就说一下遗传算法求栅格地图中机器人路径规划在每个步骤的问题、难点以及解决办法。(It is a classical problem to divide the workspace of the robot by grids and optimize the path of the robot by using optimization algorithm. At present, the ant colony algorithm is used to optimize the path on the grid map, and the genetic algorithm is used to optimize the path on the grid map, which is more difficult to achieve. The difficulties of using genetic algorithm to deal with the path planning of robot on raster map mainly include: 1. guaranteeing that the path is uninterrupted, 2. guaranteeing that the path does not cross obstacles. The steps of genetic algorithm in solving optimization problems are fixed, that is, population initialization, selection, crossover, mutation, fitness calculation. Then I will talk about the problems, difficulties and solutions of genetic algorithm in each step of robot path planning in raster map.)

ECG 信号处理源码 用于处理ECG 信号(ECG signal processing source)