MATLAB-Simulation

介绍了MATLAB中ODE的用法，希望对大家有用。(Matlab--ODE)

Wiener filter code in matlab

一种三自由度的工作空间，matlab编程代码，运行可用(Workspace of a three-degree-of-freedom, matlab programming code, run available)

说明：  matlab函数的一个例子！！就是描述扩展卡尔曼滤波的一个MATLAB算法。(this is an example about ekf!extended kalman filter algorithms applied matlab)

<精通MATLAB金融计算>随书光盘源码，对初学者很有用(Proficient in MATLAB financial calculations with CD ,)

说明：  基于OFDR的分布光纤传感技术的研究，仿真了OFDT干扰(The distributed optical fiber sensing technology based on OFDR is studied, and the ofdt interference is simulated)

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.)

MATLAB潮流计算(MATLAB flow calculation)

pattern classification homework 2

des programmes matlab