502 search results - page 38 / 101 » Computational model for amygdala neural networks |
109
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SYNASC
2005
IEEE
15 years 7 months ago
2005
IEEE
The paper presents a new reinforcement learning mechanism for spiking neural networks. The algorithm is derived for networks of stochastic integrate-and-fire neurons, but it can ...
111
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IJCNN
2007
IEEE
15 years 8 months ago
2007
IEEE
— Efficient Training in a neural network plays a vital role in deciding the network architecture and the accuracy of these classifiers. Most popular local training algorithms t...
181
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NPL
2011
14 years 4 months ago
2011
The accuracy of a model to forecast a time series diminishes as the prediction horizon increases, in particular when the prediction is carried out recursively. Such decay is faster...
104
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GECCO
2005
Springer
15 years 7 months ago
2005
Springer
Existing Recurrent Neural Networks (RNNs) are limited in their ability to model dynamical systems with nonlinearities and hidden internal states. Here we use our general framework...
134
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CIBCB
2007
IEEE
15 years 6 months ago
2007
IEEE
The accurate prediction of enzyme catalytic sites remains an open problem in bioinformatics. Recently, several structure-based methods have become popular; however, few robust seq...