小斜视角RDA

说明：  用MATLAB写的Gaussian Elimination算法即LU算法(Written using MATLAB or LU algorithm Gaussian Elimination Algorithm)

ebook about system design and modeling with simulink

原始肌肉电信号实现加噪声，频谱分析，积分肌电值求解(Muscle to achieve the original signal plus noise, spectral analysis, solving the integral EMG)

processMotion1.m MATLAB处理地震波的程序(processMotion1.m MATLAB processing seismic program)

Applied mathematical computation demonstration using matlab coding laboratory excercises

Gaussian processing regression

ecg dection component P QRST wave.

AOA定位，MUSIC算法仿真，值得一看(AOA location, the MUSIC algorithm simulation, worth a visit)

matlab的命令大全，几乎涵盖matlab的所有命令(matlab command Guinness, cover almost all the command matlab)

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.)