ML_Basic

GUI CREATING IN MATLAB EASY AND FAST

Filter high pass for processing images

state space model - john aston

在matlab编译环境下对用户界面的编译快速入门教程，对于matlab初学者比较有帮助。(In the matlab compiler environment of the user interface compiler Quick Start Guide, more helpful for matlab beginners.)

matlab时频分析工具箱，里面涵盖了大多数能用到的相关函数程序。(matlab time-frequence analysis tools box.)

bit-interleaved coded modulation with 16 QAM

This demo nstrates 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. (This demo nstrates 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. )

MATLAB 下的LDPC编码解码，自己编写，在7/0下通过验证(Decoding LDPC codes under MATLAB, I have written, in 7/0, validated)

说明：  优化常用的共轭梯度法和投影梯度法求解目标函数最优解问题(Conjugate gradient optimization of common law and the projected gradient method problems the optimal solution objective function)

matlab语言编写的算法设计程序，解决计算机映射问题(matlab language algorithm design process, problem solving computer mapping)