mix_maxlk.m

上课时做的matlab图像处理实验，包括卷积，拉普拉斯变换，罗伯特算子，种子算法，等等(Matlab class to do the image processing experiments, including convolution, Laplace transform, Robert operator, seed algorithm, and so on)

mimo信道建模，仿真结果，信道建模介绍详细说明(mimo channel modeling, simulation results, detailed description of the channel model introduced)

美股实时指数 在副图窗口，方便操作与美元有关的相关产品(US stock index for MT4)

根据遗传算法和BP神经网络理论，在MATLAB软件中编程实现基于遗传算法优化的BP神经网络非线性系统拟合算法。(According to the theory of genetic algorithm and BP neural network, in the MATLAB software programming to realize BP neural network nonlinear systems based on genetic algorithm optimization fitting method.)

compressive sensing 新版本MMA14( This is an example using the Subspace Pursuit Algorithm of Wei Dai and Olgica Milenkovic "Subspace Pursuit for Compressive Sensing: Closing the Gap Between Performance and Complexity" and the Re-weighted algorithm of Rick Chartrand and Wotao Yin "Iteratively Reweighted Algorithms for Compressive Sensing" In order to run this example you need to install all these m.files in the same directory and type trialSP2 at the prompt. Written by Igor Carron http://nuit-blanche.blogspot.com Creative Commons Licence with attribution)

fit_mix_2D_gaussian - fit parameters for a 2D mixed-gaussian distribution using EM algorithm format: [u,covar,t,iter] = fit_mix_2D_gaussian( X,M ) input: X - input samples, Nx2 vector M - number of gaussians which are assumed to compose the distribution output: u - fitted mean for each gaussian (each mean is a 2x1 vector) covar - fitted covariance for each gaussian. this is a 2x2xM matrix. t - probability of each gaussian in the complete distribution iter - number of iterations done by the function

通过matlab模拟半导体激光器的动力学特性，通过调节反馈强度可以得到从弛豫震荡到混沌态的输出信号。(Matlab simulation by the dynamics of semiconductor lasers, can be obtained by adjusting the intensity of the feedback from the chaotic state of relaxation shocks to the output signal.)

这是一个关于abaqus子程序二次开发的学习程序，其适用于初学umat的同学。(this is a secondary development for abaqus,it is a easy material model)

此文件是Weifeng Liu等编著《Kernel Adaptive Filtering A Comprehensive Introduction》一书的源代码。对应书上每一章节。是学习Kernel adaptive filter的不二选择。(This document is the source code of Liu Weifeng, a compiled book book that corresponds to each chapter. Learning kernel adaptive filter of choice.)

说明：  蚂蚁TSP算法--用蚁群算法解决旅行商问题(TSP algorithm ant ant colony algorithm to solve traveling salesman problem)