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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 ...

https://www.eeworm.com/dl/650/280629.html

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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 ...

https://www.eeworm.com/dl/650/280633.html

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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 ...

https://www.eeworm.com/dl/641/284170.html

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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 ...

https://www.eeworm.com/dl/665/284182.html

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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: ...

https://www.eeworm.com/dl/665/284186.html

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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 ...

https://www.eeworm.com/dl/641/284866.html

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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 ...

https://www.eeworm.com/dl/641/284868.html

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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 ...

https://www.eeworm.com/dl/665/284871.html

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嵌入式/单片机编程  This guide describes Freescale’s BeeKit Wireless Connectivity Toolkit configuration tool used for Zi

This guide describes Freescale’s BeeKit Wireless Connectivity Toolkit configuration tool used for ZigBee, 802.15.4, or SMAC application development. The guide describes system requirements, installation, and how to launch BeeKit. The book then guides users through a simple step-by-step process of h ...

https://www.eeworm.com/dl/647/284880.html

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VHDL/FPGA/Verilog UART发送TX控制电路设计

UART发送TX控制电路设计，以波特率产生器的EnableTX将数据DATAO以LOAD信号将其送入发送缓冲器Tbuff，并令寄存器内容已载有数据而非空出的标志tmpTBufE=0。当同步波特率信号来临时监视是否处于tmpTBufE=0（内有数据）以及tmpTRegE=1（没有数据）。即处于尚未启动发送态则将Tbuff缓冲寄存器送入传输寄存器Treg内并令tmpTRegE ...

https://www.eeworm.com/dl/663/311884.html

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