SMPP_v3_4

MEL 求解GMM模型的参数matlab环境下的源代码，和大家分享(MEL Solving GMM model parameters Matlab environment of the source code and share)

说明：  实现无功补偿选址，选址寻优ieee33节点(Reactive power compensation)

可以用来计算分歧度，这个分析度是信息论中的一个概念，类似于熵。(we can use it to calculate the klsym divergence)

平稳随机信号的参数模型功率谱估计——模型的Burg法求参数(AR-BURG)

LMI(linear matrix inequality)线性矩阵不等式工具箱利用的程序实现。一个快速入门的程序。(LMI (linear matrix inequality) using LMI toolbox program implementation. A Quick Start program.)

buck converter model

matlab codes for spatial domain filtering

本文提出了一种适用于低轨卫异扩频通信系统的多普勒频移快捕方法.该方法基于数字匹配滤波器及自动频率控制环路_利用数字匹配滤波器的囚码快捕特性及其输出主相关峰值对频偏的敏感性，缩短多普勒频移的 捕获时间.论文首先推导了多普勒频移的平均捕获时间表达式，然后根据数值分析结果得到了准最佳捕获判决策略，最后通过比较验证了该快捕方法相对于传统串行捕获方法在性能上的提高. (This paper presents a low-orbit health for different spread spectrum communication system fast catching the Doppler shift method, which based on digital matched filter and automatic frequency control loop _ prisoners using digital matched filter code features rapid acquisition and the output of the main correlation peak frequency deviation of the sensitivity of the Doppler frequency shift to shorten acquisition time. paper first derive the mean Doppler shift acquisition time expression, then the numerical results obtained quasi-optimal capture decision strategies, and finally verified by comparing with the rapid acquisition method to capture the traditional method of serial improvement in performance.)

parallel electric vehicle data set use in simulink for modelling

image inpainting (CS7495 Final Project Sooraj Bhat Object Removal by Exemplar-based Inpainting USING THE CODE Everything was done in Matlab and MEX (i.e. a C function callable from Matlab). First, the C code needs to be compiled. At the Matlab prompt, type: mex bestexemplarhelper.c You should then be able to run the following (which takes ~2mins on my 2GHz Pentium 4 laptop with 256MB of RAM): [i1,i2,i3,c,d,mov] = inpaint( bungee0.png , bungee1.png ,[0 255 0]) A smaller run (~25 seconds) would be: [i1,i2,i3,c,d,mov] = inpaint( bw0.png , bw2.png ,[0 255 0]) To visualize: plotall close movie(mov) SAMPLE IMAGES & RESULTS *0.png The original images ( bw and bungee ) *{1,2}.png The different fill region masks. *P2.png Plots of confidence and data terms. *P5.png Plots of original, fill region, inpainted images and confidence and data terms. Other images in the dir contain redundant information. I di)