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Please use this identifier to cite or link to this item: https://doi.org/10.1016/S0925-2312(97)00011-8
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dc.titleRecurrent neural networks: A constructive algorithm, and its properties
dc.contributor.authorTsoia, A.C.
dc.contributor.authorTan, S.
dc.date.accessioned2014-06-17T06:53:49Z
dc.date.available2014-06-17T06:53:49Z
dc.date.issued1997-06
dc.identifier.citationTsoia, A.C., Tan, S. (1997-06). Recurrent neural networks: A constructive algorithm, and its properties. Neurocomputing 15 (3-4) : 309-326. ScholarBank@NUS Repository. https://doi.org/10.1016/S0925-2312(97)00011-8
dc.identifier.issn09252312
dc.identifier.urihttp://scholarbank.nus.edu.sg/handle/10635/62690
dc.description.abstractIn this paper, a constructive algorithm for a general recurrent neural network is proposed based on radial basis functions. It is shown that this algorithm is globally convergent. In addition, we will present two examples to illustrate the proposed method.
dc.description.urihttp://libproxy1.nus.edu.sg/login?url=http://dx.doi.org/10.1016/S0925-2312(97)00011-8
dc.sourceScopus
dc.subjectConvergence proof
dc.subjectModified least-squares algorithm
dc.subjectOnline learning algorithm
dc.subjectRadial basis function
dc.subjectRecurrent neural networks
dc.typeArticle
dc.contributor.departmentELECTRICAL ENGINEERING
dc.description.doi10.1016/S0925-2312(97)00011-8
dc.description.sourcetitleNeurocomputing
dc.description.volume15
dc.description.issue3-4
dc.description.page309-326
dc.description.codenNRCGE
dc.identifier.isiutA1997XF18800006
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