Adaptive sliding mode approach for learning in a feedforward neural network View Full Text


Ontology type: schema:ScholarlyArticle     


Article Info

DATE

1998-12

AUTHORS

X. Yu, M. Zhihong, S. M. Monzurur Rahman

ABSTRACT

An adaptive learning algorithm is proposed for a feedforward neural network. The design principle is based on the sliding mode concept. Unlike the existing algorithms, the adaptive learning algorithm developed does not require a prioriknowledge of upper bounds of bounded signals. The convergence of the algorithm is established and conditions given. Simulations are presented to show the effectiveness of the algorithm. More... »

PAGES

289-294

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1007/bf01428120

DOI

http://dx.doi.org/10.1007/bf01428120

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1028971790


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