control-chart

横向滤波器 DFE滤波器 误码性能比较 横向滤波器 DFE滤波器 误码性能比较(横向滤波器 DFE滤波器 误码性能比较)

This is the code for vector quantization by using k-means

维纳滤波器在matlab中实现的源程序,,(weinaFilter)

To Encode the image data and compressed with important data of image

《MATLAB 7.0编程基础基础》源程序 第3章(Chapter 3 of the " MATLAB 7.0 programming foundation foundation source)

计算地震引起库伦应力改变的程序，搞应力触发的可以看看(Calculated Coulomb stress changes caused by the earthquake process)

用Matlab程序实现P阶Levinson-Durbin算法。以一个2阶自回归模型（参数为b0=1, a1=0, a2=0.81）和一个2阶滑动平均模型（参数为b0=1, b1=1, b2=1）为例，选取观测数据长度为1000，分别用一个AR(2)模型和一个AR(10)阶模型来估计其功率谱。设激励信号模型的高斯白噪声的均值为0，方差为1。用Levinson-Durbin算法迭代计算AR模型参数，并用估计出的AR模型参数画出观测信号的功率谱。并对Levinson-Durbin算法的性能进行分析。(Write a small MATLAB program that implements the pthorder Levinson-Durbin (L-D). Run/Test the program using a AR(2) process (b0=1,a1=0, a2=0.81) and an MA(2) (bn=1,1,1) process-about 1000 samples. Use L-D with p=2 (for the AR) and 10 (for the MA). Plot the AR spectra produced in the two cases with L-D. List the direct form and the reflection coefficients in a table. Profile the L-D (total number of computations for a pthorder)

自适应lms算法的两个高质量程序，结果包括等高线图，权值图等(Lms adaptive algorithm for the two high-quality procedures, and results, including contour maps, map, such as weight)

说明：  MATLAB小波分析___张德丰——源代码，对于学习小波分析很有帮助。(MATLAB Wavelet Analysis)

Algorithm Given are P training pairs {X1,d1,X2,d2....Xp,dp}, where Xi is (n*1) di is (n*1) No of Categories=R. i=1,2,...P Yi= Augmented input pattern( obtained by appending 1 to the input vector) i=1,2,…P In the following, k denotes the training step and p denotes the step counter within the training cycle Step 1: c>0 , Emin is chosen, Step 2: Weights are initialized at w at small values, w is (n+1)*1. Counters and error are initialized. k=1,p=1,E=0 Step 3: The training cycle begins here. Input is presented and output computed: Y=Yp, d=dp Oi=f(wtY) for i=1,2,….R Step 4: Weights are updated: wi=wi+1/2c(di-oi)Y for i=1,2,…..R. Step 5: Cycle error is computed: E=1/2(di-oi)2+E for i=1,2,…..R. Step 6: If p<P then p=p+1,k=k+1, and go to Step 3: Otherwise go to Step 7. Step 7: The training cycle is completed. For E=0,terminate the training session. Outputs weights and k. If E>0,then E=0 ,p=1, and enter the new training cycle by going to step 3.