getPDF1

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. )

电力系统状态估计的程序，可以进行简单的14机模型的计算(Power system state estimation procedures, a simple model for the calculation of the 14 machines)

matlab从入门到精通第8章书后源码对初学者很有帮助(matlab)

camac神经网络逼近函数,函数主要为z=(X^2+Y^2)*SIN(2*PI*X)(camac neural network approach, function primarily as z = (X ^ 2+Y ^ 2)* SIN (2* PI* X))

4-9-1的结构ga-lm的bp算法 有示例数值 不是拟合而是预测(4-9-1 structure of ga-lm bp algorithm is not fit but there are examples of numerical prediction)

windows版本—voc-release1（deformable part model），原来版本是linux版本的，但是大部分习惯用windows的，所以我讲linux版本改成了windows的，下下来在windows环境下直接可以运行(voc-release1，deformable part model (run in windows environment）)

Signal and Sytem Using Matlab 书的源代码 注释详尽 m文件(Signal and Sytem Using Matlab source code of the book documents the Notes detailed m)

绘制单架飞机（单目标）的时延多普勒关系图(Plot Delay-Doppler of single target.)

说明：  模擬分析bipolar和biphase錯誤率(Simulation of bipolar and biphase error rate)

对含有噪声的图像进行自适应方差双边滤波，与中值滤波进行比较(Consists of the noise image variance adaptive bilateral filtering, comparing with the median filtering)