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A posteriori real-time recurrent learning schemes for a recurrent neural network based nonlinear predictor

โœ Scribed by Mandic, D.P.; Chambers, J.A.

Book ID
114457544
Publisher
The Institution of Electrical Engineers
Year
1998
Tongue
English
Weight
656 KB
Volume
145
Category
Article
ISSN
1350-245X

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The following learning problem is considered, for continuous-time recurrent neural networks having sigmoidal activation functions. Given a "black box" representing an unknown system, measurements of output derivatives are collected, for a set of randomly generated inputs, and a network is used to ap