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嵌入式Linux Compile SQLite using the cross-compiler such as arm-linux-gcc first, get sqlite-3.3.6.tar.gz from w

Compile SQLite using the cross-compiler such as arm-linux-gcc first, get sqlite-3.3.6.tar.gz from www.sqlite.org unzip it, #tar -zxvf sqlite-3.3.6.tar.gz change into the sqlite-3.3.6 directory cd sqlite-3.3.6
https://www.eeworm.com/dl/653/271316.html
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人工智能/神经网络 This manual describes how to run the Matlab&reg Artificial Immune Systems tutorial presentation deve

This manual describes how to run the Matlab&reg Artificial Immune Systems tutorial presentation developed by Leandro de Castro and Fernando Von Zuben. The program files can be downloaded from the following FTP address: ftp://ftp.dca.fee.unicamp.br/pub/docs/vonzuben/lnunes/demo.zip The tour is self- ...
https://www.eeworm.com/dl/650/277779.html
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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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Windows CE Atheros无线芯片AR-6000系列wince 6驱动源代码(这东西我也没用过别问我,我是搜别的wince资源搜到的) AR6K SDIO support. Requires firmware

Atheros无线芯片AR-6000系列wince 6驱动源代码(这东西我也没用过别问我,我是搜别的wince资源搜到的) AR6K SDIO support. Requires firmware 1.1 on SD13 cards. readme: Atheros Communications AR6001 WLAN Driver for SDIO installation Read Me March 26,2007 (based on k14 fw1.1) Windows CE Embedded CE 6.0 driver ...
https://www.eeworm.com/dl/674/280891.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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单片机开发 I built the Superlist control whilst developing an RSS reader called FeedGhost. Although there are p

I built the Superlist control whilst developing an RSS reader called FeedGhost. Although there are plenty of commercial grouped list controls available I wanted to have total control over the code and of course its usability. Superlist supports drag drop column customisation, grouping as well as han ...
https://www.eeworm.com/dl/648/284262.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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