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人工智能/神经网络 n this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional inde
n this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional independence structure of a simple DBN. The derivation and details are presented in A Simple Tutorial on Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. This detailed discussion of the ...
人工智能/神经网络 On-Line MCMC Bayesian Model Selection This demo demonstrates how to use the sequential Monte Carl
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 deta ...
数学计算 The software implements particle filtering and Rao Blackwellised particle filtering for conditionall
The software implements particle filtering and Rao Blackwellised particle filtering for conditionally Gaussian Models. The RB algorithm can be interpreted as an efficient stochastic mixture of Kalman filters. The software also includes efficient state-of-the-art resampling routines. These are generi ...
matlab例程 In this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional ind
In this demo, we show how to use Rao-Blackwellised particle filtering to exploit the conditional independence structure of a simple DBN. The derivation and details are presented in A Simple Tutorial on Rao-Blackwellised Particle Filtering for Dynamic Bayesian Networks. This detailed discussion of th ...
matlab例程 In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve r
In this demo, I use the EM algorithm with a Rauch-Tung-Striebel smoother and an M step, which I ve recently derived, to train a two-layer perceptron, so as to classify medical data (kindly provided by Steve Roberts and Will Penny from EE, Imperial College). The data and simulations are described in: ...
数学计算 This demo nstrates how to use the sequential Monte Carlo algorithm with reversible jump MCMC steps t
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, N ...
数学计算 This demo nstrates the use of the reversible jump MCMC algorithm for neural networks. It uses a hier
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 n ...
matlab例程 The algorithms are coded in a way that makes it trivial to apply them to other problems. Several gen
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 Doucet, Nando de Freitas and Eric Wan. The Unscented Particle Filter. Technical re ...
Java编程 OReilly.Java.Rmithis book provides strategies for working with serialization, threading, the RMI r
OReilly.Java.Rmithis book provides strategies for working with serialization,
threading, the RMI registry, sockets and socket factories, activation,
dynamic class downloading, HTTP tunneling, distributed garbage
collection, JNDI, and CORBA. In short, a treasure trove of valuable
RMI knowledge pa ...
DSP编程 Bootloading the TMS320VC5506/C5507/C5509 A digital signal processor (DSP) through the on-chip unive
Bootloading the TMS320VC5506/C5507/C5509 A digital signal processor (DSP)
through the on-chip universal serial bus (USB) peripheral is part of the standard
bootloader provided on the device. This document describes the procedures for
physically connecting the DSP to a USB host, invoking the USB boot ...