Self-orthogonalizing strategies for enhancing Hebbian learning in recurrent neural networks
A neural network model is presented which extends Hopfield's model by adding hidden neurons. The resulting model remains fully recurrent, and still learns by prescriptive Hebbian learning, but the hidden neurons give it power and flexibility which were not available in Hopfield’s original netwo...
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| Language: | English |
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2008
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| Online Access: | http://hdl.handle.net/2429/1769 |