Full_bridge_DC_DC_BIPOLAR

与阵列信号处理理论和应用相对应的MATLAB编程，涵盖了阵列信号处理的一些采用的方法，对初学者的学习有很大的帮助。(Array signal theory and the application of the corresponding MATLAB algorithm, describes the array signal processing used in method. For beginners have a good reference value.)

block matching for motion estimation using TTS

Algorithm of Netwon and secand method

A neural network Program Fuzzy Logic versus ADALINE

这是免疫算法。这个算法几乎与遗传算法一样，只是多用了一个免疫函数 免疫算法是遗传算法的变体，它不用杂交，而是采用注入疫苗的方法。(This is the immune algorithm. This algorithm and genetic algorithm is almost the same, but with a much immune function Immune algorithm is a variant of the genetic algorithm, it does not hybridize, instead of using the method of injecting the vaccine.)

Chinese Remainder Theorem matlab

说明：  基于盲返卷积方法，恢复被噪声污染的图像，利用matlab实现。(Blind return convolution methods to restore the image of the noise pollution, the use of matlab.)

IMC-PID是利用内模控制原理来对PID参数进行计算，应用小区域方差对比，程序简单，一个师兄的毕设。( The IMC- PID is using the internal model control principle for PID parameters is calculated, Application of small area variance comparison, simple procedures, A complete set of brothers.)

通过卷积码的学习，建立了卷积码的两种译码方式的simulink仿真模型！(in this part we can use the simulink to realize the convolutional decoding by harddecision and softdecision.)

1.duishuzhengtai：产生对数正态分布 2.gaussian：产生数据量为n的两个相互独立高斯分布y1、y2 3.junyun：自定义 0-1的均匀分布，n代表数据量，一般要大于1024（蒙特卡罗） 4.ruili：瑞利分布,m是瑞利分布的参数,n代表数据量,n一般要大于1024 5.kaifeng：产生开丰分布，其中m代表开丰分布的自由度，n表示产生的点数量 6.tfenbu：本函数产生自由度为m，数据量为n的t分布。 7.weibuer：a=1时,是指数分布；a=2时,是瑞利分布(1.duishuzhengtai: generating lognormal 2.gaussian: generating a data quantity n of two mutually independent Gaussian distribution Y1, Y2 3.junyun: custom uniform distribution of 0-1, n represents a data amount, generally large in 1024 (Monte Carlo) 4.ruili: Rayleigh distribution, m is a parameter of the Rayleigh distribution, n representative of the amount of data, n is generally greater than 1024 5.kaifeng: generating open abundance distribution, wherein m represents an open-abundance distribution freedom of degrees of freedom, n is the number of points generated 6.tfenbu: This function generates m, the amount of data for n t distribution. 7.weibuer: a = 1, the exponential distribution a = 2, is a Rayleigh distribution)