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Discrete-Time Analogs for a Class of Continuous-Time Recurrent Neural Networks

โœ Scribed by Liu, Pingzhou; Han, Qing-Long


Book ID
121835873
Publisher
IEEE
Year
2007
Tongue
English
Weight
457 KB
Volume
18
Category
Article
ISSN
1045-9227

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โœ Eduardo D. Sontag ๐Ÿ“‚ Article ๐Ÿ“… 1998 ๐Ÿ› Elsevier Science ๐ŸŒ English โš– 117 KB

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