Referenced Items are not available for this document.
We derive two second-order algorithms, based on the conjugate gradient method, for online training of recurrent neural networks. These algorithms use two different techniques to extract second-order information on the Hessian matrix without calculating or storing it and without making numerical approximations. Several simulation results for nonlinear system identification tests by locally recurrent neural networks are reported for both the off-line and online case
Published in:
Neural Networks Proceedings, 1998. IEEE World Congress on Computational Intelligence. The 1998 IEEE International Joint Conference on
(Volume:1
)
Date of Conference: 4-8 May 1998
- Page(s):
- 384 - 389 vol.1
- Meeting Date :
- 04 May 1998-09 May 1998
- ISSN :
- 1098-7576
- Print ISBN:
- 0-7803-4859-1
- INSPEC Accession Number:
- 6033685
- Conference Location :
- Anchorage, AK
- Digital Object Identifier :
- 10.1109/IJCNN.1998.682297
- Product Type:
- Conference Publications
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