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Description: 该文档较为详细的讲述了如何实现fortran语言与matlab接口的问题-the document in detail about how to achieve the FORTRAN language and Matlab interface issues
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Author: fsc03 |
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Description: 马尔可夫链,蒙特卡洛方法,数值模拟 matlab程序-Markov chain Monte Carlo methods, numerical simulation procedures Matlab
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Author: 俏鱼 |
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Description: This demo nstrates the use of the reversible jump MCMC simulated annealing for neural networks. This algorithm enables us to maximise the joint posterior distribution of the network parameters and the number of basis function. It performs a global search in the joint space of the parameters and number of parameters, thereby surmounting the problem of local minima. It allows the user to choose among various model selection criteria, including AIC, BIC and MDL
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Size: 958464 |
Author: 大辉 |
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Description: 该程序为基于粒子滤波的一种新算法,综合MCMC Bayesian Model Selection即MONTE CARLO马尔克夫链的算法,用来实现目标跟踪,多目标跟踪,及视频目标跟踪及定位等,解决非线性问题的能力比卡尔曼滤波,EKF,UKF好多了,是我珍藏的好东西,现拿出来与大家共享,舍不得孩子套不着狼,希望大家相互支持,共同促进.-the program based on particle filter for a new algorithm, Integrated Bayesian MCMC Model Selection MONTE CARLO that Ma Erkefu chain algorithm, which can be used for target tracking, multi-target tracking, and video tracking and positioning. solve nonlinear problems of capacity than Kalman filtering, EKF, UKF much better, and I treasure the good stuff, now up with the share could not bear children, she sets the wolf, we hope that support each other and work together to promote.
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Size: 14336 |
Author: zhang |
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Description: 关于pf,ekf,ukf,upf,epf,并加上mcmc算法-On pf, ekf, ukf, upf, epf, and together with the MCMC algorithm
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Size: 63488 |
Author: wang meng |
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Description: semi-supervised MCMC classification
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Size: 20480 |
Author: 刘国亮 |
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Description: mcmc 马尔可夫链 蒙特卡罗算法
具体参数 请用help命令-MCMC Markov chain Monte Carlo algorithm specific parameters Please help command
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Description: 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.
-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.
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Size: 16384 |
Author: 徐剑 |
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Description: This demo nstrates 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.-This demo nstrates 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.
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Size: 220160 |
Author: 晨间 |
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Description: 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.
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Size: 348160 |
Author: 晨间 |
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Description: 这是马尔可夫-蒙特卡罗算法的MATLAB源程序.-This is the Markov- Monte Carlo algorithm for MATLAB source code.
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Size: 136192 |
Author: liufanmao |
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Description: 大家可以参考的例子滤波源码,程序非常好用,能里脊肉粒子滤波的基础-Everyone can refer to examples of source filtering, the program is very easy to use, can fillet the basis of particle filter
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Size: 15360 |
Author: 周迎 |
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Description: 针对无线传感器网络的节点的追踪算法matlab仿真。-For wireless sensor network nodes tracking algorithm matlab simulation.
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Size: 14336 |
Author: 王东 |
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Description: 马尔科夫链蒙特卡洛模拟的matlab源代码-Markov chain Monte Carlo simulation of the matlab source code
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Size: 16384 |
Author: 左秀霞 |
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Description: mcmc 马尔科夫蒙塔卡罗模拟,模拟随机过程-mcmc markarv motecalo simulation
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Size: 20480 |
Author: layui |
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Description: MCMC方法,代码, MCMC方法,代码-MCMC code,MCMC code,MCMC code,MCMC code
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Size: 14336 |
Author: li hongwei |
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Description: 蒙特卡洛方法的MATLAB的m文件,看看有用没有-Monte Carlo method of MATLAB m-files to see if there is no useful
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Size: 15360 |
Author: 李小明 |
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Description: 马尔可夫链蒙特卡洛方法在matlab中的实现程序-Markov chain Monte Carlo method in the realization of program matlab
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Size: 19456 |
Author: 陈文军 |
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Description: matlab MCL(蒙特卡罗)仿真,移动节点-matlab MCL (Monte Carlo) simulation, mobile nodes
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Size: 16384 |
Author: xzli |
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Description: 可逆挑转马尔科夫链门特卡洛算法实现代码(在matlab下实现的)-Reversible Markov chain transfer gate pick Teka Luo algorithm code (in matlab under implementation)
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Size: 39936 |
Author: linda |
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