CS_OMP

解决旅行商，解决旅行商解决旅行商解决旅行商解决旅行商解决旅行商(TO SOLVE T。S。P)

数值分析算法matlab：清华大学出版社数值分析课后实验计算题9个matlab程序和实验报告(Numerical_Analysis_of_algorithms matlab)

关于PCA的仿真数据生成及故障信噪比（SNR）的主元选取方法仿真代码。(About PCA generated simulation data and fault signal to noise ratio (SNR) of the main element simulation code selection method.)

用拉丁超立方采样方法模拟具有相关性的数组代码(Latin Hypercube Sampling Method cubic correlated array simulation code)

基于MATLAB的图像处理（设计图形用户界面，图像直方图统计和直方图均衡）(MATLAB-based image processing (the design of graphical user interface, image histogram statistics and histogram equalization))

说明：  用matlab实现的神经网络Hopfield网络算法，初步编写，欢迎指正(nertural network)

基于无迹卡尔曼滤波的人工神经网络matlab程序(Similar to using the extended Kalman filter, Neural Networks can also be trained through parameter estimation using the unscented Kalman filter. This file provides a function for this purpose. It also includes an example to show how to use this function.)

可逆跳跃马尔科夫蒙特卡洛贝叶斯模型选择，主要用于神经网络(Reversible Jump MCMC Bayesian Model Selection This demo demonstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural networks. This model treats the model dimension (number of neurons), model parameters, regularisation parameters and noise parameters as random variables that need to be estimated. The derivations and proof of geometric convergence are presented, in detail, in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Robust Full Bayesian Learning for Neural Networks. Technical report CUED/F-INFENG/TR 343, Cambridge University Department of Engineering, May 1999. After downloading the file, type "tar-xf rjMCMC.tar" to uncompress it. This creates the directory rjMCMC containing the required m files. Go to this directory, load matlab5 and type "rjdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.)

safari调用第三方APP demo 可以直接调试成功 供新手参考 (safari called third-party APP demo success can be directly debug reference for the novice)

说明：  传统MUSIC算法仿真，有很高的应用价值，也存在很多的误差，有待深入研究(Conventional MUSIC algorithm simulation, the application has a very high value, there are many errors to be in-depth study)