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用于心电信号滤波，峰值检测，相位检测中值检测(For ECG filtering, peak detection, phase detection value Detected)

在Matlab下用Simulink进行通信仿真，模拟线性调制，扰码与解扰，低通信号的抽样定理设计 (In Matlab using Simulink for communication simulation, simulation of linear modulation, scrambling and descrambling, low-signal design of the sampling theorem)

Ensemble修改程序，包括源程序和调用程序及实例。(Ensemble modify the program, including the source and call procedures and examples.)

说明：  用MATLAB可视化编程界面实现简单的二维函数作图(Visual programming interface with MATLAB simple two-dimensional mapping function)

典型磁滞模型的的matlab m文件编程，对初学者很有帮助(Typical model of hysteresis of matlab m file programming, to beginners helpful )

Signal processing front end for extracting the feature set is an important stage in any speech recognition system. The optimum feature set is still not yet decided. There are many types of features, which are derived differently and have good impact on the recognition rate. This paper presents one more successful technique to extract the feature set a speech signal, which can be used in speech recognition systems. Our technique based on the human auditory system characteristics and relies on the gammachirp filterbank to emulate asymmetric frequency response and level dependent frequency response.

运用Matlab，对一些对比度较差的图片进行目标物提取时使用的阈值方法，其中，其运用的是动态阈值的方法（非全局阈值）(Using Matlab, for some poor contrast image target extraction using threshold method, among them, the use of a dynamic threshold method (not a global threshold value))

各种方法的去噪程序 den1.m 使用半软阈值方法对图像进行去噪 den1_5_1.m 半软阈值的改进方法 对第一层重构图像进行均值滤波 den1_9.m 半软阈值的改进方法 将线性衰减的函数改为指数的 den1_10.m 半软阈值的改进方法 对第一层的重构图像再次进行小波阈值去噪 den2.m 用软硬阈值函数的改进方法进行去噪 den3.m 用广义阈值函数进行去噪 den4.m 用自适应特征阈值函数进行去噪 wdenoise.m 用Donoho阈值或Birge-Massart策略及软阈值或硬阈值函数进行去噪 meanfilter.m 均值滤波方法进行去噪(对比用) medfilter.m 中值滤波方法进行去噪(对比用)(Denoising procedures for various methods Den1.m using semi soft threshold method for image denoising The improved method of den1_5_1.m semi soft threshold for the first layer of the reconstructed image The improved method of den1_9.m semi soft threshold will be changed linear to exponential. The improved method of den1_10.m semi soft threshold for the first layer of the reconstructed image again for wavelet thresholding denoising Den2.m using the soft and hard threshold function to improve the method of denoising Den3.m using generalized threshold function for denoising Den4.m with adaptive feature threshold function for denoising Wdenoise.m with Donoho threshold or Birge-Massart strategy and soft threshold or hard threshold function for denoising Meanfilter.m mean filtering method for denoising (contrast) Medfilter.m median filtering method for denoising (contrast))

D-S证据理论以及D-S证据合成规则matlab实现 封装成函数简单易用(D-S evidence theory & D-S evidence synthesis matlab programing)

Monte Carlo方法的实质是通过大量随机试验，利用概率论解决问题的一种数值方法，基本思想是基于概率和体积间的相似性。它和Simulation有细微区别。单独的Simulation只是模拟一些随机的运动，其结果是不确定的；Monte Carlo在计算的中间过程中出现的数是随机的，但是它要解决的问题的结果却是确定的。(The essence of the Monte Carlo method is a numerical method to solve the problem through a large number of randomized trials, the use of probability theory, the basic idea is based on the similarity between the probability and volume. There are subtle differences between it and Simulation. Separate the Simulation simulation of random movement, the result is uncertain number of the Monte Carlo calculations in the middle of the process is random, but it is to solve the problem the result is determined.)