DP

mimo-ofdm系统仿真，输出仿真图，信道脉冲响应实部虚部随信噪比变化时的改变图(mimo-ofdm system simulation, simulation output figure, the channel impulse response changes in real and imaginary parts of the map changes with SNR)

此代码是svm的源码，可利用此程序进行支持向量机的分类处理(This code is the source code of svm, which can be used to classify support vector machines.)

小波去噪的压缩包，用matlab编程，对去噪有用(Wavelet packet denoising of compression, using matlab programming, useful for the denoising)

Dynamic Modeling and Simulation of a Small Wind-Fuel Cell Hybrid Energy System

Simulation of spring mass use Simulink matlab

Simple lorem ipsum generator

数字图像处理中的Arnold变换和反变换的MATLAB实现程序,附Lenna图片一张。(Matlab program for Arnold transfer and invers Arnold transfer in digital image processing with a picture of Lenna. )

这个程序是用来仿真多小区多用户，已知信道信息，采用OFDM，QPSK调制下的误码性能分析，特点是将预编码参数放在频域处理。(This program is used to simulate multi-user multi-cell, known channel information, using OFDM, QPSK modulation BER performance under analysis, is characterized by the pre-coding parameters on the frequency domain.)

eye tracking with matlab

说明：  它主要研究的是多因变量对多自变量的回归建模，特别当各变量内部高度线性相关时，用偏最小二乘回归法更有效。另外，偏最小二乘回归较好地解决了样本个数少于变量个数等问题。 偏最小二乘法是集主成分分析、典型相关分析和多元线性回归分析3种分析方法的优点于一身。它与主成分分析法都试图提取出反映数据变异的最大信息，但主成分分析法只考虑一个自变量矩阵，而偏最小二乘法还有一个“响应”矩阵，因此具有预测功能。(It is mainly a result of the study is a multi-variable regression modeling and more independent variables, especially when the internal height of each variable linear correlation, partial least squares regression method is more effective. In addition, partial least squares regression solves the number of samples is less than the number of variables and other issues. Partial least squares method is a set of principal component analysis, canonical correlation analysis and multiple linear regression analysis of the advantages of the three methods in one. It is the principal component analysis are trying to extract the maximum information reflects data variability, but the principal component analysis considers only one independent variable matrix, and partial least squares and a &quot response&quot matrix, predictive capabilities.)