meilin

说明：  非线性最小二乘优化问题以误差的平方和最小为准则来估计非线性静态模型参数的一种参数估计方法。设非线性系统的模型为y=f(x，θ)，常用于传感器参数设定。(64/5000 A parameter estimation method based on the minimum sum of squares of errors. Suppose that the model of the nonlinear system is y=f(x,), which is commonly used for sensor parameter setting.)

蒙特卡罗算法,本人做毕业设计时用的! 有兴趣的可以交流!(Monte Carlo algorithm, I graduated to do the design used! Are interested in the exchange!)

控制工具箱与SIMULINK软件应用：系统对象为G(s)=4/s(s+2) PI补偿器K1(s)=(s+1)/s K2(s)=(s+0.5)/s a 若由K1(s)与 G(s)串联组成的单位反馈系统，称为系统A。 b 若由K1(s) 放置在G(s)的反馈通道称为系统B。 c 若由K2(s)与G(s)串联组成的单位称为系统C，绘制上述每一种情况的阶跃响应与斜坡响应，求每一种情况下的系统阶跃响应误差与斜坡响应误差，并与理论分析结果进行比较。 (Control toolbox and SIMULINK software application: system object for G (s) = 4/s (s+ 2) PI compensator K1 (s) = (s+ 1)/s K2 (s) = (s+ 0.5)/s If a by K1 (s) and G (s) series of feedback system of the unit, known as a system a. B if the K1 (s) placed in G (s) feedback channel called system b. If c by K2 (s) and G (s) series of unit is called system c, draw the above each kind of condition of step response and slope response, for each of these cases system step response error and slope response error, and the results were compared with theoretical analysis.)

function [r_path, r_cost] = dijkstra(pathS, pathE, transmat) The Dijkstra s algorithm, Implemented by Yi Wang, 2005 This version support detecting _cyclic-paths_

基于LMS的自适应滤波与维纳滤波的性能比较(Performance comparison of LMS-based adaptive filtering and Wiener filtering)

利用二维小波分析对图像进行压缩。一个图像作小波分解后，可得到一系列不同分辨率的子图像，不同分辨率的子图像对应的频率是不相同的。(failed to translate)

基于LMS算法的噪声对消程序，设定了正弦信号，及噪声(LMS noise cancellation Set in a sinusoidal signal, and noise)

利用fisher准则设计一个分类器并在matlab上仿真实现检验其功能(Fisher guidelines to design a classifier and simulation test its function in matlab)

信号y=sin(2*pi*f1*t)+sin(2*pi*f2*t)加上信噪比为2高斯白噪声的傅里叶变换，分别画出时域和频域图(Signal y = sin (2* pi* f1* t)+ sin (2* pi* f2* t) plus noise ratio for two Gaussian white noise of the Fourier transform, respectively, to draw the time domain and frequency domain)

This program code is used for compressing a content or image using LZW compression methods.