VoiceSeperationFastICA

Matlab code for face recognition eigen and fischer faces

说明：  一、 简介 本仿真软件可以仿真波片对偏振光的相位调制过程。用户可以通过改变波片的类型，波片长轴与X轴的夹角，起偏器透光与X轴的夹角，检偏器透光轴与X轴的夹角等参数，来观察屏上光强及透过波片后的偏振光的信息。 建议在Matlab2008a或以上平台上运行本软件。 (I. Introduction The simulation software can simulate wave plate for polarization phase modulation process. Users can change the type of wave plate, wave plate angle between the long axis and the X-axis, from the transmission side device and the X-axis angle, the transmission axis of the polarizer angle between the X-axis parameters to the viewing screen glazing strong and polarized light through the wave plate information. Recommended Matlab2008a or run the software on the platform above.)

说明：  matlab code about image processing

Aprendizagem de maquina - Um exemplo utilizando SVM

基于红外图像的弱小目标检测与跟踪，本程序是基于局域概率分布的小目标检测(Based on infrared image small target detection and tracking, this program is based on a small target detection probability distribution of local)

这一段代码是基于matlab的仿真编程，主要是针对16QAM的调制，代码及其仿真结果无不从各个方面详细分析了技术原理。(This piece of code is based on the Matlab simulation programming for 16QAM modulation, code and its simulation results are all from the various aspects of a detailed analysis of the technical principles.)

lms算法实现滤波，重构权值，对噪声信号进行重构，可以实现时延计算(LMS algorithm filtering, reconstruction of the right value, the noise signal reconstruction, time-delay calculation can be achieved)

根据给定的函数，分别用复合梯形公式、复合辛普森公式、龙贝格求积公式和变步长的求积公式计算积分结果，并且比较积分的精确度。(According to a given function, namely, composite trapezoidal formula using composite Simpson formula Romberg quadrature formula and the variable step-size integration quadrature formula results, and compare the accuracy of points.)

使用MATLAB和VC6进行混合编程的教程(Mixed use of MATLAB and programming tutorials VC6)

信号去噪的基本步骤： （1）信号的小波分解； （2）小波分解高频系数的阈值量化； （3）信号的小波重构。使用分解的低频系数以及阈值量化后的高频系数进行小波重构。 (The basic steps of signal denoising:( 1) of the wavelet decomposition of signals ( 2) the high frequency coefficients of wavelet decomposition threshold quantization ( 3) the signal wavelet reconstruction. Using the decomposition of the low frequency coefficient and threshold quantization the high-frequency coefficient after wavelet reconstruction.)