vad

形状分割，采用指标为短轴与长轴之比，骨架复杂度。效果很好，预处理合理(Shape segmentation, the use of indicators for the short axis and long axis ratio, frame complexity. Good effect, pre-rational)

说明：  matlab的qpsk-fading的程序代码 是初学者的福音(The qpsk-fading matlab program code is the gospel for beginners)

直接序列扩频源程序,对于研究扩频的朋友十分有益，请大家下载！(the code of DSSS，It s very good for study DSSS)

基于matlab的pca人脸识别，非常精确，快下哦(pca face recognition, very precise, fast under Oh! !)

freespace1_1_ABC(added1_2) Electromagnetic Simulation using the FDTD method 书后实例。matlab重新编写(freespace1_1_ABC(added1_2)Electromagnetic Simulation using the FDTD method examples,rewriting in matlab.)

基于神经网络的双色球预测，采用滑动窗口对输入参数进行了处理(Shuangseqiu forecast based on neural network, a sliding window on the input parameters are processed)

理论力学问题——大角度单摆的MATLAB模拟(Theory of mechanical problems- MATLAB simulation of large-angle pendulum)

给出一段噪声音乐信号，用滑动平均滤波器进行处理，观察改变滑动窗口宽度对声音效果的影响。 （1）读取一段噪声信号，画出未处理噪声信号的时域波形和信号频谱图； （2）在Matlab中利用滑动平均滤波器对噪声信号进行处理，得出处理后的图像； （3）改变滑动窗口的宽度，观察处理后噪声以及图像得出对效果的影响。(A piece of noise music signal is given. It is processed with a sliding average filter to observe the effect of changing the width of sliding window to the sound effect. (1) a noise signal is read and the time domain waveform and signal spectrum map of the unprocessed noise signal are drawn. (2) in Matlab, a sliding mean filter is used to process the noise signal, and the image after processing is obtained. (3) to change the width of the sliding window, to observe the noise after processing and to the effect of the image.)

基于MATLAB的近似熵程序,主要用与生物信号的检测,主要用于生物医疗工程的信号处理方面(matlab program for calculating approximate entropy in biomedical signal processing especially.)

多种概率分布的拟合函数集合 本算法包括最大似然估计，最小二乘估计，基于EM算法的多种混合高斯分布估计，EM算法测试实例，绘制每种分布的plot函数。非常有参考价值！(Fitting a wide range of probability distribution functions including the collection of this algorithm maximum likelihood estimation, least squares estimation, based on the EM algorithm estimate a mixture Gaussian distribution, EM algorithm for the test examples, each mapping the distribution of the plot function. Have reference value is!)