shuixiangshuiweimohukongzhi

这是matlab入门的相关重要例程,对接触不久的朋友非有用哈.(This is the relevant entry-matlab important routines, Friend of the near contact of non-useful Kazakhstan.)

应用matlab程序，实现了对手写数字的识别，准确率非常高。(Matlab application procedures, to achieve the hand-written digit recognition, the accuracy rate is very high.)

EEG signal analysez in matlab We hope to useful

处理质谱曲线warping的一个GUI程序，很不错-MS treatment warping curve a GUI program, it is good(a GUI to deal with mass spectrometry figure )

matlab空间后方交会程序 实现空间后方交会程序(matlab space resection procedure)

FDTD for Wave equation1

原创的，使用vc++实现匀速运动模型（constant velocity）的kalman滤波，可以运行，并有matlab测试程序对滤波结果进行对比。(vc++ constant velocity kalman filter。the matlab m file can obervers the filter results)

Matlab book for beginer

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.)

使用高阶累积量对MPSK信号进行调制识别，可实现对二维数据的聚类，迭代自组织数据分析。( Using high-order cumulants of MPSK signal modulation recognition, Can realize the two-dimensional data clustering, Iterative self-organizing data analysis.)