Visualization_4d

说明：  有详细说明的手编模拟退火法及其示例，为TXT文件，复制到指定M文件即可运行(Detailed description of the hand for example, simulated annealing and for the TXT file, copy the file to run the specified M)

将图像进行主成分分析，并显示第一主成分，方法很好用的(The principal component analysis is performed and the first principal component is displayed.)

Hybrid Multilevel Inverter

Chevyshev algoritmo de filtro

Complex Color Noise Generator based on Allan Variance coefficients (MatLab function)

说明：  基于小波变化的一些程序，有效的提高语音识别(Some of the procedures based on wavelet transform, effectively improve the speech recognition)

水下信号与信息处理中，为了准确估计方位，把波束分为左右两路波束，成为虚拟阵元，然后计算方位。(Underwater signal and information processing, in order to accurately estimate the orientation of the beam into two beams around and become virtual array, and then calculate the position.)

说明：  分别应用jacobi迭代和gseid迭代进行方程的求解，并且比较两种迭代方法的精度 和效率(Were applied jacobi iteration to iteration and gseid equation, and compare the two precision and efficiency of iterative methods)

Seismic analysis just for fun

In computer science, particle swarm optimization (PSO) is a computational method that optimizes a problem by iteratively trying to improve a candidate solution with regard to a given measure of quality. PSO optimizes a problem by having a population of candidate solutions, here dubbed particles, and moving these particles around in the search-space according to simple mathematical formulae over the particle s position and velocity. Each particle s movement is influenced by its local best known position but, is also guided toward the best known positions in the search-space, which are updated as better positions are found by other particles. This is expected to move the swarm toward the best solutions.