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嵌入式Linux This program is distributed in the hope that it will be useful, ** but WITHOUT ANY WARRANTY without

This program is distributed in the hope that it will be useful, ** but WITHOUT ANY WARRANTY without even the implied warranty of ** MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE. See the ** GNU General Public License for more details.

https://www.eeworm.com/dl/653/245310.html

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人工智能/神经网络  Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form

Boosting is a meta-learning approach that aims at combining an ensemble of weak classifiers to form a strong classifier. Adaptive Boosting (Adaboost) implements this idea as a greedy search for a linear combination of classifiers by overweighting the examples that are misclassified by each classifie ...

https://www.eeworm.com/dl/650/252976.html

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matlab例程  This program simulates plant identification using frequency block least mean square (FBLMS) alogrith

This program simulates plant identification using frequency block least mean square (FBLMS) alogrithm reference: 《LMS算法的频域快速实现》 LMS is modified by XXX in XXX place, see details in XXX relevant document

https://www.eeworm.com/dl/665/265510.html

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软件设计/软件工程  Scotia Airlines is a new budget airline operating between Glasgow Airport and the Western Isles. It

Scotia Airlines is a new budget airline operating between Glasgow Airport and the Western Isles. It operates two 24-seater light passenger aircraft and requires a flight booking system. Because Scotia offers low cost air travel, there is a need to treat each flight as single cost centre and to be ab ...

https://www.eeworm.com/dl/684/275551.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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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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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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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 ...

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