piddata

User Manual for STABLE 5.1(This manual gives information about the STABLE library, which computes basic quantities for univariate stable distributions: densities, cumulative distribution functions, quantiles, and simulation. Statistical routines are given for fitting stable distributions to data and assessing the fit. Utility routines give information about the program and perform related calculations. Quick spline approximations of the basic functions are provided. Densities, cumulative distribution functions and simulation for discrete/quantized stable distributions are described. The multivariate module gives functions to compute bivariate stable densities, simulate stable random vectors, and fit bivariate stable data. In the radially symmetric case, the amplitude densities, cumulative distribution functions, quantiles are computed for dimension up to 100. The signal filtering module includes functions to compute non-linear filters for signals with heavy tailed noise. Specifically, a novel stable fi)

MULTILETARION FOR TRACKING

压缩感知OMP重构算法，误差很小，完美重构，信号由多个信号叠加而成(Compression-aware OMP reconstruction algorithm, the error is very small, perfect reconstruction, the signal a number of signals stacked)

说明：  it is a very good way to use matlab simulink for analysis of control systems in nature

说明：  协同网络中继选择算法 一种是基于门限的最大信噪比选择；另一种是基于门限的最小误码率选择，我们将选择一条最佳的中继链路和源节点到目的节点的直接传输链路在目的端进行最大比合并(Research on relay selection algorithm in cooperative wireless Networks)

包括各种频域滤波器：经典频域理想低通滤波器 ，经典频域巴特沃斯低通滤波器 ，经典频域指数低通滤波器， 经典频域理想高通滤波器 ， 经典频域巴特沃斯高通滤波器， 经典频域指数高通滤波器,经典频域带通滤波器 ,经典频域带阻滤波器(Including a variety of frequency domain filter: Classic ideal low-pass filter frequency domain, frequency domain classic Butterworth low-pass filter, the classic low-pass filter frequency domain index, the classic ideal high-pass filter frequency domain, frequency domain Butterworth classic Andean high-pass filter, the classic high-pass filter frequency domain index, the classical frequency domain band-pass filter, band stop filter frequency domain classics)

K均值聚类是模式识别中非常重要的一种方法，通过K均值聚类可以将具有相同属性的元素进行聚合。(K-means clustering is a very important one in the pattern recognition method, polymerization by K-means clustering with the elements of the same property.)

针对EMD经验模态分解不能找到instfreq的问题(For empirical mode decomposition EMD can not find instfreq problems)

MATLAB GUI代码，设计了一个适用于FTIR和动态箱组数据分析(MATLAB GUI Code)

neural network codes for gates