XINHAOmatlab

实现小波包能量分解（6层分解），且易于参考从而编写出小波能量分解。(Implementation of wavelet packet energy decomposition (decomposition of 6-layer), and easy-to-reference to the preparation of a wavelet decomposition of energy.)

说明：  《用S变换做精细时变滤波》本篇文章对于理解s变换在地震资料处理上的应用非常有帮助(err)

接收端采用的算法和程序流程与发送端发送的OFDM符号的帧结构有关系。具体的帧结构，以及定时估计，频偏估计，剩余误差跟踪的算法可参考算法说明文档。这里对程序的流程进行说明。 首先根据短训练字的特性进行相关运算，进行信号到达检测，当检测到相关值大于门限一定次数后，认为有信号到达。然后根据长训练字的特性，进行相关运算，进行OFDM符号FFT窗口起始位置的估计。估计出FFT窗口的位置后，先在时域进行小频偏的估计，将两个长训练字进行小频偏补偿后，进行FFT运算，根据FFT运算的结果进行整数倍频偏的估计。这些参数估计完成后，就可以进行数据解调了。先对数据部分进行完整的频偏补偿，然后根据估计的FFT窗口位置进行FFT运算得到频域的数据，进行解调。然后在对应于导频的子载波位置上提取出导频信息，根据导频信息估计出剩余定时误差以及剩余的信道响应误差，将误差量送入环路进行跟踪。当收到所有数据后，重新回到信号到达检测状态，进行下一次信号到达的检测和信号接收。 (The receiving end uses the algorithm and the program flow and the frame structure of the OFDM symbol transmitted by the sending end. Specific frame structure, and timing estimation, frequency offset estimation, residual error tracking algorithm can refer to the documentation. Here to illustrate the process of the program. First, according to the characteristics of the short training word correlation operation, the signal reaches the detection, when the correlation value is greater than the threshold of a certain number of times, that there is a signal to reach. Then, according to the characteristics of the long training word, the correlation operation is carried out, and the initial position of the OFDM symbol FFT is estimated. The estimated position of the FFT window, first in the time domain for small frequency offset estimation, two long training word for small frequency offset compensation, the FFT operation. According to the result of FFT for integer frequency bias estimation. Af)

说明：  一个简单的卡尔曼滤波代码，matlab编写，供初学者借鉴(A simple Kalman filter code, matlab prepared for beginners learn)

这段程序是关于图像分析中的各种颜色处理的，感兴趣的同学可以看看(This program is all about the color of the image analysis processing, interested students can look)

实现机械故障在线检测， 实时控制，叶片裂纹的检测控制与报警。使得企业或者使用人员很方便的观测机械的故障并及时修正。(Mechanical fault diagnosis system)

协同微粒群算法，用于原子簇的结构优化。协同微粒群算法模型由南非人Frans van den Bergh提出，对高维问题处理的效果要显著优于基本微粒群算法。(synergies PSO algorithm, for the cluster of structural optimization. Synergy PSO algorithm model from South Africa who Frans van den Bergh, for the high-dimensional problems of the effect was significantly better than the basic particle swarm algorithm.)

数学建模的模型建立方面的书籍资料拿来与大家分享，还算比较经典吧(Model of mathematical modeling of the information used books to share with you, it is still relatively classic)

Matlab+GUI编程中文参考手册，讲的很具体(Reference of Matlab+GUI)

overlapping speech segments