On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps to perform model selection in neural networks. We treat both the model dimension (number of neurons) and model parameters as unknowns. The derivation and details are presented in: Christophe Andrieu, Nando de Freitas and Arnaud Doucet. Sequential Bayesian Estimation and Model Selection Applied to Neural Networks . Technical report CUED/F-INFENG/TR 341, Cambridge University Department of Engineering, June 1999. After downloading the file, type "tar -xf version2.tar" to uncompress it. This creates the directory version2 containing the required m files. Go to this directory, load matlab5 and type "smcdemo1". In the header of the demo file, one can select to monitor the simulation progress (with par.doPlot=1) and modify the simulation parameters.
标签： demonstrates sequential Selection Bayesian
上传时间： 2016-04-07
上传用户：lindor
本文简要介绍一种基于Monte Carlo模型和时隙驱动相结合的WCDMA R99 HSDPA网络规划仿真模型，并通过该模型对一则案例在动态功率分配和静态功率分配情况下分别进行仿真。在最后部分，文章给出仿真结果，讨论联合载频和独立载频吞吐量差别，并分析功率分配方式对下行吞吐量和资源利用率的影响。
上传时间： 2013-11-08
上传用户：ljmwh2000
超宽带系统链路matlab仿真程序 超宽带系统简单仿真平台，有简单界面.包括可替换的脉冲成型（半余弦脉冲）、IEEE802.15.3a的修正SV信道、最大似然信道估计、Rake接收机等模块，可以实现monte carlo仿真求误码率。可添加多址接入、编码等功能（维特比编解码、帧同步的程序由本人同学编写）。入口主程序uwbsim.m 编解码程序：bin2deci.m；bini2deci.m；deci2bin.m VITRBI.m 信道及信道估计：ch_est.m；channel.m；channelgenerator.m；conv_m. m；sigfold.m UWB_SV_channel.m uwb_sv_cnvrt_ct.m uwb_sv_eval_ct.m uwb_sv_model_ct.m uwb_sv_params.m Rake接收机：findpeak.m；MRC_combine.m；MRC_Rake.m；n_upsample.m；selectpath.m 其他：cnv_encd.m；dssignal.m；Eb_halfcos.m；waveshape.m；halfcos_generator.m；metric.m；nxt_stat.m；sim_main.m；spreadgren.m；test_code.m；training_ds.m；uwbsim.m；vit_test.m
上传时间： 2013-12-30
上传用户：duoshen1989
Electromagnetic scattering from the trees above a tilted rough ground plane generated by the stochastic Lidenmayer system is studied by Monte Carlo simulations in this paper.The scattering coefficients are calculated in three methods:coherent addition approximation,tree-independent scattering,and independent scattering.
标签： Electromagnetic scattering generated the
上传时间： 2013-12-06
上传用户：xieguodong1234
Klaas Gadeyne, a Ph.D. student in the Mechanical Engineering Robotics Research Group at K.U.Leuven, has developed a C++ Bayesian Filtering Library that includes software for Sequential Monte Carlo methods, Kalman filters, particle filters, etc.
标签： Engineering Mechanical Robotics Research
上传时间： 2015-09-07
上传用户：Altman
自己编写的超宽带系统简单仿真平台，有简单界面.包括可替换的脉冲成型（半余弦脉冲）、IEEE802.15.3a的修正SV信道、最大似然信道估计、Rake接收机等模块，可以实现monte carlo仿真求误码率。可添加多址接入、编码等功能（维特比编解码、帧同步的程序由本人同学编写）。入口主程序uwbsim.m 编解码程序：bin2deci.m；bini2deci.m；deci2bin.m VITRBI.m 信道及信道估计：ch_est.m；channel.m；channelgenerator.m；conv_m. m；sigfold.m UWB_SV_channel.m uwb_sv_cnvrt_ct.m uwb_sv_eval_ct.m uwb_sv_model_ct.m uwb_sv_params.m Rake接收机：findpeak.m；MRC_combine.m；MRC_Rake.m；n_upsample.m；selectpath.m 其他：cnv_encd.m；dssignal.m；Eb_halfcos.m；waveshape.m；halfcos_generator.m；metric.m；nxt_stat.m；sim_main.m；spreadgren.m；test_code.m；training_ds.m；uwbsim.m；vit_test.m
上传时间： 2013-12-15
上传用户：redmoons
Uniform random number generators by Agner Fog, 2001 - 2007 randomc.zip contains a C++ class library of uniform random number generators of good quality. The random number generators found in standard libraries are often of a poor quality, insufficient for large Monte Carlo calculations. This C++ implementation provides random number generators of a much better quality: Better randomness, higher resolution, and longer cycle lengths. The same random number generators are available as libraries coded in assembly language for higher speed. These libraries can be linked into projects coded in other programming languages under Windows, Linux, BSD, etc. The library files are available in the archive asmlib.zip. Non-uniform random number generators are provided in stocc.zip.
标签： generators contains Uniform randomc
上传时间： 2014-12-01
上传用户：royzhangsz
Computes BER v EbNo curve for convolutional encoding / soft decision Viterbi decoding scheme assuming BPSK. Brute force Monte Carlo approach is unsatisfactory (takes too long) to find the BER curve. The computation uses a quasi-analytic (QA) technique that relies on the estimation (approximate one) of the information-bits Weight Enumerating Function (WEF) using A simulation of the convolutional encoder. Once the WEF is estimated, the analytic formula for the BER is used.
标签： convolutional Computes encoding decision
上传时间： 2013-12-24
上传用户：咔乐坞
pMatlab is a toolsbox from MIT for running matlab in parallel style on a multi-core PC or a cluster environment. These two documents summary the usage of pMatlab and running time measurements on three simple Monte Carlo simulation codes.
标签： multi-core toolsbox parallel pMatlab
上传时间： 2014-12-05
上传用户：zhliu007
The package includes 3 Matlab-interfaces to the c-code: 1. inference.m An interface to the full inference package, includes several methods for approximate inference: Loopy Belief Propagation, Generalized Belief Propagation, Mean-Field approximation, and 4 Monte-Carlo sampling methods (Metropolis, Gibbs, Wolff, Swendsen-Wang). Use "help inference" from Matlab to see all options for usage. 2. gbp_preprocess.m and gbp.m These 2 interfaces split Generalized Belief Propagation into the pre-process stage (gbp_preprocess.m) and the inference stage (gbp.m), so the user may use only one of them, or changing some parameters in between. Use "help gbp_preprocess" and "help gbp" from Matlab. 3. simulatedAnnealing.m An interface to the simulated-annealing c-code. This code uses Metropolis sampling method, the same one used for inference. Use "help simulatedAnnealing" from Matlab.
标签： Matlab-interfaces inference interface the
上传时间： 2016-08-27
上传用户：gxrui1991
