gmrpd-0.1.1

《MATLAB 7.X程序设计》-王建卫-源代码及习题答案 ( MATLAB 7.X program design - Wang Wei- the source code and answer exercises)

说明：  有限元分析基础教程,曾攀,清华大学研究生实用教材(Finite element analysis based tutorials, have climbed, Tsinghua University, teaching graduate students and practical)

说明：  实现资料预测，输入训练集数据和测试集数据可以得到对应的均方根误差(Realization data prediction)

VLSi projet....these were recent papers published in ieee

dc motor speed control using fuzzy logic

运用matlab编写DNN程序，带有几个实例，有BP神经网络，relu，sigmod等~(Using matlab to write DNN program, with several examples, such as BP neural network, relu, sigmod, etc.~)

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. )

这一个music 的DOA算法，可以说通俗易懂，结果也十分完美。我比较骄傲的一个。(music doa)

system radar in simulink

最小二乘算法来实现esprit算法，该代码已经在matlab中运行过绝对可以放心使用(Least squares algorithm to achieve esprit algorithm, the code has been run in matlab absolutely safe to use)