Comparison of neural models, off-line and on-line learning algorithms for a benchmark problem

Ruano, Antonio

http://hdl.handle.net/10400.1/2290

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Authors

Ruano, Antonio

Abstract(s)

This papcr comparcs thc application of diffcrcnt ncural modcls-multilaycr pcrccptrons, radial basis functions and B-splincs - for a bcnchmark problem, and illustrates the applicability of a common learning algorithm for all models considered. The learning algorithm is employed both for off-line training and for on-line model adaptation. In the latter case. a sliding window of past learning data is employed.

URI

http://hdl.handle.net/10400.1/2290

Citation

Ruano, A. E. B. Comparison of Neural Models, Off-line and On-line Learning Algorithms for a Benchmark Problem, In Artificial Neural Nets Problem Solving Methods, 457-464, ISBN: 978-3-540-40211-4. Berlin, Heidelberg: Springer Berlin Heidelberg, 2003.