StockAnalysis

cidial code matlab code

在matlab的环境下实现了自回归移动平均模型（arima）(Matlab environment in the realization of the auto-regressive moving average model (arima))

说明：  用MATLAB仿真PID控制，其中用simulink建仿真模型，用matlab语言编写PSO算法用于优化PID参数整定。(Matlab is used to simulate PID control, in which Simulink is used to build simulation model, and PSO algorithm is written in MATLAB language to optimize PID parameter setting.)

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.)

Simulated annealing MATLAB code with an example

LVQ神经网络的分类——乳腺肿瘤诊断，MATLAB的经典算法(LVQ neural network classification- breast cancer diagnosis, MATLAB classical algorithm)

SAR signal processing

Matlab高阶统计量工具箱函数中文文档(Higher-order statistics Matlab toolbox functions Chinese documents)

详尽地介绍了sparse sensing 和morpological Componet Analysis的内容(these introduce sparse sensing and morpological Componet analysis)

A matlab implementation of the KNN classifier. It is tested and working well.