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基于有限单元法的三角剖分圆的MATLAB程序(Finite element method based on triangulation of the circle MATLAB program)

虚拟激励法程序 用于结构工程领域的地震工程分析(Pseudo-excitation method for structural engineering procedures for earthquake engineering analysis)

this is the telatar paper.

说明：  用FDTD计算二维光子晶体带隙的Matlab的源程序(the calculation of band gap of 2D photonic crystals by Matlab language )

Particle in cell 方法的matlab代码，非常基础，算例是空间存在一带电平板情况下，等离子体的电场分布和离子密度分布。作为入门非常好。(Particle in cell method matlab code, very basic, there is a numerical example is charged under the flat space case, the electric field distribution of plasma and ion density distribution. As entry is very good.)

多级最小二乘参数估计算法，能够估计ARX结构的模型的参数(multi-level least square parameter estimation algorithm, suitable for estimating the parameters of an ARX model)

三层平板介质光波导计算，该平板波导主要由3层均匀介质构成，中间的芯层折射率为n1，厚度为d，芯区生长在折射率为n2的衬底上，芯区上面的覆盖层折射率为n3。这里考虑的是n1大于n2大于n3。(Three-layer flat-plate dielectric waveguide, the flat waveguide is composed of three uniform media, the refractive index of the middle layer is n1, the thickness is d, the core area is grown on the substrate with refractive index n2, The refractive index of the layer is n3. It is considered here that n1 is greater than n2 and greater than n3.)

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. )

说明：  在这种程序列表中的主要文件是“vblast.m”。键入“help VBLAST系统”关于details.Study通过该方案由步进编码的命令行。(In this process the main file list is &quot vblast.m&quot . Type &quot help VBLAST System&quot on details.Study stepping through the program from the command line coding.)

this program solves an Income Fluctuation Problem requires obj.m function which is the RHS of the Bellman equation as a function of c=consumption and x=cash in hand