MPID

AR自回归模型，主要介绍时间序列分析中重要的一个模型。(AR autoregression model, time series analysis introduces an important model.)

滞环电流模块，可用于伺服电机来仿真使用，效果很好！(Hysteresis current module can be used to simulate the use of servo motors, the effect is very good!)

matlab code for Command-line peak fitting function for time-series signals

Source code for Radial basic function for classification

sumt法，具有二次收敛性，若目标函数为二次正定函数，经有限步可达到极小点(sumt method, with quadratic convergence, if the objective function is quadratic positive definite function can be achieved by the finite step minima)

该函数能够实现保存Matlab GUI中axes控件图像的功能(this function can save pictures from axes controls in Matlab GUI)

A COM based interface that allows you to call R functions from within MATLAB. The functions are: openR - Connect to an R server process. evalR - Run an R command. getRdata - Copies an R variable to MATLAB. putRdata - Copies MATLAB data to an R variable. closeR - Close connection to R server process. Rdemo - An example of using R from withing MATLAB.

使用matlab编写的各种类型的遗传算法，每一种都有注释说明 可以复制到M文件中运行(Matlab prepared using various types of genetic algorithms, each with explanatory notes can be copied to M to run in files)

贝叶斯分类器，基于最小错误率的贝叶斯分类器(Bayes)

文件中包含word文档报告 设雷达采用匹配滤波完成脉冲压缩，采集频率fs=420MHz，仿真雷达回波，并绘出家Hamming窗前后的脉压波形。（提示：通过正确设定采集波门，减少数据量） 设雷达采用Dechirp方式完成脉冲压缩，其中参考距离位于（0，0），采集频率为10MHz，距离采样点数512点，仿真雷达回波，并绘出加Hamming窗前后的脉压波形（提示：通过正确设定采集波门，减少数据量）。(Word document file contains the report of the completion of matched filter-based radar uses pulse compression, gathering frequency fs = 420MHz, simulation of radar echo, and draw the house after the pulse pressure waveform Hamming window. (Hint: By setting the correct collection wave door, reducing the amount of data), based radar uses pulse compression Dechirp manner, in which reference distance at (0,0), collection frequency of 10MHz, from the sampling points 512 points, simulation, radar echo, and draw the increase of pulse pressure waveform after the Hamming window (hint: set up collection waves through the correct door, reducing the amount of data).)