RC4_run

时间域建模，matlab提供了三种时间域建模函数，在这个压缩包里面分别叙述。(Time domain modeling, matlab provides three time-domain modeling functions, in this compressed packet which are described separately.)

此程序包含心音信号的低通滤波、小波去噪、EMD分解、希尔伯特黄变换以及心音阈值定位一系列算法。输入为采集到的单通道心音信号。入口程序为main.m (A program that process heart sound signals to separete each heart sound clearly.Functions like Low-pass filters and Hilbert transformers are involed.)

Dynamical Systems with Applications using MATLAB书附带免费源代码(It covers standard material for an introduction to dynamical systems theory. The text deals with both discrete and continuous systems.)

三相三线制两电平APF数学模型的MATLAB编程实现，输入为三桥臂的开关函数，输出为三相电流和直流侧电压(Three-phase three-wire APF system for the two-level mathematical model of the MATLAB programming)

压缩感知中全变分（TV）重构算法，本程序主要用于图像重构(Total variation in the compressed sensing (TV) reconstruction algorithm, this procedure is mainly used for image reconstruction)

独立分量分析的开关算法代码 ，内有pdf格式说明文挡 希望有用(independent component analysis algorithm code switch, which shows a pdf format text block useful hope)

pid matlab 实用例程2(详细讲解个PId的matlab编程)(PID-matlab applictional example 2)

通过傅里叶变换的方法，对两个单频信号的相位差进行计算，信号相关性计算(Fourier transform method, the phase difference between two single-frequency signal is calculated)

Compressive sampling is an emerging technique that promises to effectively recover a sparse signal from far fewer measurements than its dimension. The compressive sampling theory assures almost an exact recovery of a sparse signal if the signal is sensed randomly where the number of the measurements taken is proportional to the sparsity level and a log factor of the signal dimension. Encouraged by this emerging technique, this thesis briefly reviews the application of Compressive sampling in speech processing. It comprises the basic study of two necessary condition of compressive sensing theory: sparsity and incoherence. In this thesis, various sparsity domain and sensing matrix for speech signal and different pairs that satisfy incoherence condition has been compiled.

该函数用来计算时间序列的最大Lyapunov 指数--Wolf 方法(This function is used to calculate the maximum Lyapunov exponent of time series- Wolf Method)