pa021

moro转换算法，将0-1均匀分布转换为标准正态分布(moro conversion algorithm will convert the 0-1 uniform distribution to standard normal distribution)

说明：  （拟合） 用给定的多项式，y=x3-6x2+5x-3，产生一组数据(xi,yi，i=1,2,…,n),再在yi上添加随机干扰(可用rand产生(0,1)均匀分布随机数,或用rands产生N(0,1)分布随机数)，然后用xi和添加了随机干扰的yi作的3次多项式拟合，与原系数比较。 如果作2或4次多项式拟合，结果如何？ ((Fitting) with a given polynomial, y = x3-6x2+5 x-3, generated a set of data (xi, yi, i = 1,2, ..., n), then add a random disturbance yi ( can be generated rand (0,1) uniformly distributed random number, or rands generated N (0,1) distribution of random numbers), and then added with xi and yi for random interference of the 3 times polynomial fitting, and the original coefficient. If 2 or 4 times for polynomial fitting, the result?)

这是具有功率因数校正的开关电源的MATLAB/SIMULINK仿真模型，希望对有用的人，有所帮助！(this is a simulink model of power supply with PFC, which is useful for those who study on this!)

designing of low pass filter using matlab

该程序使用MATLAB编程实现目标标记的功能，并将图像与黑色背景叠加转化为二值图像(The program uses the MATLAB programming function of the target tag and the image is superimposed with a black background image into a binary)

Vector Templates for Handprinted Symbol Recognition

这是偶自己的作品拉，基于matlab环境，作的图象压缩实验，分别ＤＷＴ与ＳＷＴ作对比参照实验(This is the duality gap own work, based on the matlab environment, for the image compression experiments, DWT and SWT, respectively, compared with reference to experimental)

OFDM信号瑞利衰落信道的matlab仿真代码，,包括一个word文档和仿真程序。(OFDM signals in Rayleigh fading channel simulation matlab code, including a word document and simulation program.)

这个程序是在matlab环境下编写的，通过对两幅图像分析，然后进行模板匹配(This program is written in the matlab environment, through the analysis of two images, and then template matching)

信道估计,we will assume that the receiver knows your name, i.e., it knows s (and of course x). Based on this knowledge, the receiver will estimate h using the MVU and MMSE method (for the latter it is also assumed that the variance of the noise σ2 is known at the receiver).(Channel Estimation:we will assume that the receiver knows your name, i.e., it knows s (and of course x). Based on this knowledge, the receiver will estimate h using the MVU and MMSE method (for the latter it is also assumed that the variance of the noise σ2 is known at the receiver).)