liziqun_Matlab

MATLAB版的SVM，使用相对于C来比较的方便，可以试一试(MATLAB version of the SVM, the use of vis-à-vis C to compare the convenience, you can try)

程序1实现线性相位FIR低通滤波器； 程序2实现线性相位FIR高通滤波器； 程序3实现用kaiser窗实现带通滤波器。(Program to achieve a linear phase FIR low-pass filter Program 2 for linear phase FIR high-pass filter Program 3 Achieved bandpass filter with a kaiser window)

差分编码的实现、信噪比、误码率等等的实现，并且有截图，比较详细的资料。(Differential encoding implementation, SNR, BER, etc. to achieve, and there are shots, more detailed information.)

说明：  音频水印在复倒谱域嵌入水印，采用统计均值调制方法嵌入(Audio watermarking in the complex cepstrum domain embedded watermark embedding using statistical average modulation method)

toolbox de MatLab, de analisis lineal discriminante

hilbert-huang 变换分析一段脉搏波 运行maihht即可(hilbert- KE3 transform a pulse wave can run maihht)

描述HIV 扩散，其有独特的传播路径，通过MATLAB仿真模拟，可以很生动的发现规律。(Description HIV proliferation, the spread of its unique path through MATLAB simulation, can be very vivid discovery rule.)

Relief算法中特征和类别的相关性是基于特征对近距离样本的区分能力。算法从训练集D中选择一个样本R，然后从和R同类的样本中寻找最近邻样本H，称为Near Hit，从和R不同类的样本中寻找最近样本M，称为Near Miss，根据以下规则更新每个特征的权重： 如果R和Near Hit在某个特征上的距离小于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻是有益的，则增加该特征的权重；反之，如果R和Near Hit在某个特征上的距离大于R和Near Miss上的距离，则说明该特征对区分同类和不同类的最近邻起负面作用，则降低该特征的权重。(The correlation between feature and category in Relief algorithm is based on distinguishing ability of feature to close sample. The algorithm selects a sample R from the training set D, and then searches for the nearest neighbor sample H from the samples of the same R, called Near Hit, and searches for the nearest sample M from the sample of the R dissimilar, called the Near Miss, and updates the weight of each feature according to the following rules: If the distance between R and Near Hit on a certain feature is less than the distance between R and Near Miss, it shows that the feature is beneficial to the nearest neighbor of the same kind and dissimilar, and increases the weight of the feature; conversely, if the distance between R and Near Hit is greater than the distance on R and Near Miss, the feature is the same. The negative effect of nearest neighbor between class and different kind reduces the weight of the feature.)

Pattern recognition using matlab software had a very good simulation, the use of Bayesian Classifiers for boys and girls had a very good classification.

this program is to use Bayesian algorithms to achieve a treatment process