baudrate

电力系统单机无穷大系统的仿真，包括三相短路单相短路(Single machine infinite bus power system)

这是HEED协议的源代码，根据论文的描述缩写，基本实现了论文的功能，但是有些微小的出入。(HEED protocol source code, according to the paper' s description of abbreviations, the basic functionality of papers, but some minor discrepancies.)

matlab图像特征提取程序。。。图像特征统计及计算(matlab image feature extraction procedures. . . Statistics and computing image features)

基于MATLAB平台实现利用FFT计算线性卷积(MATLAB-based platform for the realization of the linear convolution calculation using FFT)

this code is developed in matlab for different sound using wavelets

matlab数值分析计算源代码，供广大研究者学习(Numerical Analysis matlab source code, for the majority of researchers to learn)

space vector modulation with simulink

这是读取segy文件的matlab程序，对matlab中数学建模计算有着重要的作用(This matlab program read segy file.)

Smooths a matrix (with/without NaN s) via recursive moving average method and eliminates data gaps. (MOVING_AVERAGE(X,F) smooths the vector data X with a boxcar window of size 2F+1, i.e., by means of averaging each element with the F elements at his right and the F elements at his left. The extreme elements are also averaged but with less data, obviously. Leaving the edges intact. The method is really fast. MOVING_AVERAGE2(X,M,N) smooths the matrix X with a boxcar window of size (2M+1)x(2N+1), i.e., by means of averaging each element with its surrounding elements that fits in the mentioned box centered on it. This one is also really fast. The elements at the edges are averaged too, but the corners are left intact. NANMOVING_AVERAGE(X,F) or NANMOVING_AVERAGE(X,F,1) accept NaN s elements in the vector X the latter interpolates also those NaN s elements surrounded by numeric elements. NANMOVING_AVERAGE2(X,M,N) or NANMOVING_AVERAGE2(X,M,N,1) accept elements NaN s in the matrix X the latter interpolates also those NaN elements surrounded by numeric elements.)

I developed an algorithm for using local ICA in denoising multidimensional data. It uses delay embedded version of the data, clustering and ICA for the separation between data and noise. (I developed an algorithm for using local ICA in denoising multidimensional data. It uses delay embedded version of the data, clustering and ICA for the separation between data and noise.)