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Data
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Robust Reservoir Generation by Correlation-Based Learning (Yamazaki & Tanaka 2008)
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"Reservoir computing (RC) is a new framework for neural computation.
A reservoir is usually a recurrent neural network with fixed random connections.
In this article, we propose an RC model in which the connections in the reservoir are modifiable.
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We apply our RC model to trace eyeblink conditioning.
The reservoir bridged the gap of an interstimulus interval between the conditioned and unconditioned stimuli, and a readout neuron was able to learn and express the timed conditioned response."
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tyam@brain.riken.jp
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Tadashi Yamazaki and Shigeru Tanaka, Robust Reservoir Generation by Correlation-Based Learning, Advances in Artificial Neural Systems, vol. 2009, Article ID 467128, 7 pages, 2009. doi:10.1155/2009/467128 http://www.hindawi.com/GetArticle.aspx?doi=10.1155/2009/467128
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73
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