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  1. rjMCMCsa

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  2. 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 dim
  3. 所属分类:其它资源

    • 发布日期:2008-10-13
    • 文件大小:16.04kb
    • 提供者:徐剑
  1. On-Line_MCMC_Bayesian_Model_Selection

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  2. 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
  3. 所属分类:其它资源

    • 发布日期:2008-10-13
    • 文件大小:214.89kb
    • 提供者:晨间
  1. Reversible_Jump_MCMC_Bayesian_Model_Selection

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  2. 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 param
  3. 所属分类:其它资源

    • 发布日期:2008-10-13
    • 文件大小:340.61kb
    • 提供者:晨间
  1. rjMCMCsa

    0下载:
  2. 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 dim
  3. 所属分类:人工智能/神经网络/遗传算法

    • 发布日期:2024-12-23
    • 文件大小:16kb
    • 提供者:徐剑
  1. On-Line_MCMC_Bayesian_Model_Selection

    0下载:
  2. 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
  3. 所属分类:数学计算/工程计算

    • 发布日期:2024-12-23
    • 文件大小:215kb
    • 提供者:晨间
  1. Reversible_Jump_MCMC_Bayesian_Model_Selection

    0下载:
  2. 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 param
  3. 所属分类:数学计算/工程计算

    • 发布日期:2024-12-23
    • 文件大小:340kb
    • 提供者:晨间
  1. MCMC_Unscented_Particle_Filter_demo

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  2. The algorithms are coded in a way that makes it trivial to apply them to other problems. Several generic routines for resampling are provided. The derivation and details are presented in: Rudolph van der Merwe, Arnaud Do
  3. 所属分类:matlab例程

    • 发布日期:2024-12-23
    • 文件大小:57kb
    • 提供者:晨间
  1. upf_demos

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  2. 无香粒子滤波的一个matlab例程,其中有ekf,ukf,pf,upf-In these demos, we demonstrate the use of the extended Kalman filter (EKF), unscented Kalman filter (UKF), standard particle filter (a.k.a. condensation, survival of the fittest, boots
  3. 所属分类:matlab例程

    • 发布日期:2024-12-23
    • 文件大小:38kb
    • 提供者:gaofei
  1. rjMCMCsa

    1下载:
  2. 可逆跳跃马尔科夫蒙特卡洛贝叶斯模型选择,主要用于神经网络-Reversible Jump MCMC Bayesian Model Selection This demo demonstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hierarchical full Bayesian model for neural
  3. 所属分类:matlab例程

    • 发布日期:2024-12-23
    • 文件大小:17kb
    • 提供者:gaofei

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