On-line Gauss-Newton-based learning for fully recurrent neural networks

DOI10.1016/J.NA.2005.02.015zbMath1167.68433OpenAlexW2153910709MaRDI QIDQ999616

A. A. Vartak, Michael Georgiopoulos, Georgios C. Anagnostopoulos

Publication date: 4 February 2009

Published in: Nonlinear Analysis. Theory, Methods \& Applications. Series A: Theory and Methods (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/j.na.2005.02.015

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05)

Cites Work

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• On the improvement of the real time recurrent learning algorithm for recurrent neural networks
• A conjugate gradient learning algorithm for recurrent neural networks
• A normalised real time recurrent learning algorithm.
• Numerical Optimization

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