viterbi_tmpl

matlab和optisystem调试用的幅度调制程序，在optisystem里面使用matlab组件然后使用。(matlab and optisystem debugging with the amplitude modulation process, component and then use the optisystem inside Matlab.)

系统辨识，节拍延迟线（TDL）模型，PRN序列，蒙特卡洛仿真次数(System identification, beats delay line (TDL) model, PRN sequences, Monte Carlo simulation times)

利用Mersenne Twister算法产生随机数，并测试和分析了其随机性。 程序中还加入了界面显示。 各个文件为： initGenerator.m： initGenerator函数，用于初始化随机序列的长度和值 generateNum.m: generateNum函数，当index为0时被调用，用于创建624维的移位寄存器数组 extractNum.m: extractNum函数，根据index当前值选择数组中的数生成随机数，同时改变index的值。 main.m: main主函数，输入种子seed和产生数目total，输出产生结果及随机性测试结果 mymy.m和mymy.fig: 用于界面显示的部分，这两个文件会通过界面传入seed和total的值，并调用main函数，在相应的框中显示输出结果。 (According to the algorithm principle on Wikipedia, the Mersenne Twister algorithm to generate random numbers, and test and analysis of its randomness. The program has also joined the interface display. The individual files are: initGenerator.m: initGenerator function used to initialize the random sequence length and value generateNum.m: generateNum function is invoked when the index is zero, and used to create a 624-dimensional shift register array extractNum.m: extractNum function, according to index the current value to select the number to generate random numbers, and change the value of the index in the array. main.m: main function of the input seed to seed and produce the number of total, the output generated results and the randomness of the test results mymy.m and mymy.fig: Part of these two files for interface display interface incoming seed and the total value of, and calls the main function, to display the output in the appropriate boxes.)

Lucas-Kanade光流法，计算两幅图像之间的光流，很有用的一段程序(Lucas-Kanade optical flow method to calculate the optical flow between two images, very useful for some procedures)

提取音频的mfcc特征值 是一个matlab函数 直接调用即可(Extract audio mfcc characteristic value is a matlab function can be called directly)

时间序列工具箱，包括时间序列分析的各种MATLAB源代码。(time series toolbox)

coding for non parametric two way ANalysis Of VAriance

基于matlab对GM模型进行测算，此模型为GM预算模型，原理为GM1.1模型原理(Matlab-based estimates of the GM model, the model budget for the GM model, the principle of GM1.1 model theory)

自写策略，MA均线突破，20日均线和50日均线突破的策略，仅供参考(MA20 & MA50 STRATEGY)

运用matlab工具箱的神经网络遗传算法函数进行极值寻优-非线性函数极值(Matlab neural network using genetic algorithm toolbox function optimization Extreme- Extreme nonlinear function)