{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,1,24]],"date-time":"2026-01-24T06:55:51Z","timestamp":1769237751990,"version":"3.49.0"},"reference-count":17,"publisher":"Elsevier BV","issue":"1","license":[{"start":{"date-parts":[[2003,4,1]],"date-time":"2003-04-01T00:00:00Z","timestamp":1049155200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Mathematics and Computers in Simulation"],"published-print":{"date-parts":[[2003,4]]},"DOI":"10.1016\/s0378-4754(02)00159-3","type":"journal-article","created":{"date-parts":[[2003,4,7]],"date-time":"2003-04-07T14:47:43Z","timestamp":1049726863000},"page":"1-13","source":"Crossref","is-referenced-by-count":16,"title":["On-line RBFNN based identification of rapidly time-varying nonlinear systems with optimal structure-adaptation"],"prefix":"10.1016","volume":"63","author":[{"given":"Giorgos","family":"Apostolikas","sequence":"first","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Spyros","family":"Tzafestas","sequence":"additional","affiliation":[],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"78","reference":[{"key":"10.1016\/S0378-4754(02)00159-3_BIB1","first-page":"321","article-title":"Multivariable function interpolation and adaptive networks","volume":"2","author":"Broomhead","year":"1988","journal-title":"Complex Syst."},{"key":"10.1016\/S0378-4754(02)00159-3_BIB2","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1162\/neco.1990.2.2.210","article-title":"Layered neural networks with Gaussian hidden units as universal approximators","volume":"2","author":"Hartman","year":"1990","journal-title":"Neural Comput."},{"issue":"3","key":"10.1016\/S0378-4754(02)00159-3_BIB3","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1109\/72.761725","article-title":"Reformulated radial basis neural networks trained by gradient descent","volume":"10","author":"Karayiannis","year":"1999","journal-title":"IEEE Trans. Neural Netw."},{"key":"10.1016\/S0378-4754(02)00159-3_BIB4","doi-asserted-by":"crossref","first-page":"247","DOI":"10.1109\/72.661120","article-title":"Radial basis function networks and complexity regularization in function learning","volume":"9","author":"Krzyzak","year":"1998","journal-title":"IEEE Trans. Neural Netw."},{"key":"10.1016\/S0378-4754(02)00159-3_BIB5","doi-asserted-by":"crossref","unstructured":"C.T. Lin, Neural Fuzzy Control Systems with Structure and Parameter Learning, World Scientific, Singapore, 1994.","DOI":"10.1142\/2225"},{"key":"10.1016\/S0378-4754(02)00159-3_BIB6","doi-asserted-by":"crossref","first-page":"281","DOI":"10.1162\/neco.1989.1.2.281","article-title":"Fast learning in locally-tuned processing units","volume":"1","author":"Moody","year":"1989","journal-title":"Neural Comput."},{"key":"10.1016\/S0378-4754(02)00159-3_BIB7","doi-asserted-by":"crossref","first-page":"819","DOI":"10.1162\/neco.1996.8.4.819","article-title":"On the relationship between generalization error, hypothesis complexity, and sample complexity for radial basis functions","volume":"8","author":"Niyogi","year":"1996","journal-title":"Neural Comput."},{"issue":"3","key":"10.1016\/S0378-4754(02)00159-3_BIB8","doi-asserted-by":"crossref","first-page":"334","DOI":"10.1109\/72.97910","article-title":"An adaptively trained neural network","volume":"2","author":"Park","year":"1991","journal-title":"IEEE Trans. Neural Netw."},{"key":"10.1016\/S0378-4754(02)00159-3_BIB9","doi-asserted-by":"crossref","first-page":"246","DOI":"10.1162\/neco.1991.3.2.246","article-title":"Universal approximation using radial-basis-function networks","volume":"3","author":"Park","year":"1991","journal-title":"Neural Comput."},{"key":"10.1016\/S0378-4754(02)00159-3_BIB10","doi-asserted-by":"crossref","first-page":"305","DOI":"10.1162\/neco.1993.5.2.305","article-title":"Universal approximation and radial basis function networks","volume":"5","author":"Park","year":"1993","journal-title":"Neural Comput."},{"issue":"3","key":"10.1016\/S0378-4754(02)00159-3_BIB11","doi-asserted-by":"crossref","first-page":"657","DOI":"10.1109\/72.377971","article-title":"On-line learning with minimal degradation in feedforward networks","volume":"6","author":"Ruiz de Angulo","year":"1995","journal-title":"IEEE Trans. Neural Netw."},{"key":"10.1016\/S0378-4754(02)00159-3_BIB12","doi-asserted-by":"crossref","unstructured":"S.G. Tzafestas, Y. Anthopoulos, Supervised learning in multilayer perceptrons: the back-propagation algorithm, in: S.G. Tzafestas (Ed.), Soft Computing in Systems and Control Technology, World Scientific, Singapore, 1999, pp. 3\u201330.","DOI":"10.1142\/9789812816528_0001"},{"issue":"2","key":"10.1016\/S0378-4754(02)00159-3_BIB13","first-page":"257","article-title":"Self tuning multivariable fuzzy and neural control using genetic algorithms","volume":"21","author":"Tzafestas","year":"2000","journal-title":"J. Inform. Optimiz. Sci."},{"issue":"2","key":"10.1016\/S0378-4754(02)00159-3_BIB14","first-page":"130","article-title":"Nonlinear neural control of discrete-time systems using local model neural networks","volume":"4","author":"Tzafestas","year":"2000","journal-title":"Int. J. Knowledge-Based Intell. Eng. Syst."},{"key":"10.1016\/S0378-4754(02)00159-3_BIB15","doi-asserted-by":"crossref","unstructured":"S.G. Tzafestas, D. Vogiatzis, Concerning Hopfield networks: an overview with application to system identification and control, in: S.G. Tzafestas (Ed.), Computational Intelligence in Systems and Control Design and Applications, Kluwer, Dordrecht, 1999, pp. 311\u2013334.","DOI":"10.1007\/978-94-010-9040-7"},{"key":"10.1016\/S0378-4754(02)00159-3_BIB16","doi-asserted-by":"crossref","first-page":"609","DOI":"10.1016\/0893-6080(94)90040-X","article-title":"On radial basis function nets and kernel regression: approximation ability, convergence rate and receptive field size","volume":"7","author":"Xu","year":"1994","journal-title":"Neural Netw."},{"issue":"2","key":"10.1016\/S0378-4754(02)00159-3_BIB17","doi-asserted-by":"crossref","first-page":"202","DOI":"10.1049\/ip-cta:19970891","article-title":"Identification of time-varying nonlinear systems using minimal radial basis function networks","volume":"144","author":"Yingwei","year":"1997","journal-title":"IEE Proc. Control Theory Appl."}],"container-title":["Mathematics and Computers in Simulation"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0378475402001593?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0378475402001593?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2019,4,2]],"date-time":"2019-04-02T02:27:07Z","timestamp":1554172027000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0378475402001593"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2003,4]]},"references-count":17,"journal-issue":{"issue":"1","published-print":{"date-parts":[[2003,4]]}},"alternative-id":["S0378475402001593"],"URL":"https:\/\/doi.org\/10.1016\/s0378-4754(02)00159-3","relation":{},"ISSN":["0378-4754"],"issn-type":[{"value":"0378-4754","type":"print"}],"subject":[],"published":{"date-parts":[[2003,4]]}}}