CMA_Equalizer

循环码和BCH码的matlab编程，还有详细的算法过程(Cyclic codes and BCH codes matlab programming, as well as detailed algorithm process)

这是解调中重要的DDS恢复部分，做成子函数形式，具体的输入输出变量已经表明，请按介绍使用。谢谢站长(This is the most important part, DDS, causing Functions form specific input and output variables have shown, click on the use. Thank you, Captain! !)

adding noise and removeing point processing drawing histogram histogram equalization histogram matching spatial filtering

Processor architecture in single document

MATLAB程序，用小波变换的方法实现Haar分解与重构。(MATLAB program, the method used to achieve Haar wavelet transform decomposition and reconstruction.)

压缩感知源代码，观测矩阵采用哈达吗变换。很好的入门代码(Compressed sensing the source code, you transform observation matrix using Hada. Good entry code)

说明：  基于模拟退火算法的TSP问题解算方法和二维路径规划(Based on simulated annealing algorithm for TSP solution method and two-dimensional path planning)

基于字典学习的语音增强中字典更新的算法，称作近似K-SVD算法，其中包含了OMP算法用于稀疏编码计算系数矩阵(Dictionary-based learning dictionary speech enhancement algorithm update, called approximate K-SVD algorithm, which contains the sparse coding algorithm is used to calculate the coefficient matrix OMP)

说明：  连续信号的相关于褶积。本程序在matlab上已经测试，可以直接调用。(Continuous signal related to the convolution. This procedure has been tested in matlab can be called directly.)

粒子群算法，也称粒子群优化算法（Particle Swarm Optimization），缩写为 PSO， 是近年来发展起来的一种新的进化算法(（Evolu2tionary Algorithm - EA）。PSO 算法属于进化算法的一种，和遗传算法相似，它也是从随机解出发，通过迭代寻找最优解，它也是通过适应度来评价解的品质，但它比遗传算法规则更为简单，它没有遗传算法的“交叉”(Crossover) 和“变异”(Mutation) 操作，它通过追随当前搜索到的最优值来寻找全局最优。这种算法以其实现容易、精度高、收敛快等优点引起了学术界的重视，并且在解决实际问题中展示了其优越性。(Particle swarm optimization, also known as particle swarm optimization (Particle Swarm Optimization), abbreviated as PSO, is a new evolutionary algorithm developed in recent years ((Evolu2tionary Algorithm- EA) .PSO algorithm is an evolutionary algorithm, and similar genetic algorithm, it is also starting random solutions, through iterative search for the optimal solution, which is also uated by the quality of the fitness solution, but it is much simpler than genetic algorithms rule, it does not have the genetic algorithm cross (Crossover) and variant (Mutation) operation, which by following the current search to find the optimal value to the global optimum. the algorithm for its easy implementation, high accuracy, and fast convergence advantages attracted academic attention, and in solving practical problems demonstrated its superiority.)