An implementation and initial test of generalized radial basis functions Public Deposited

http://ir.library.oregonstate.edu/concern/graduate_thesis_or_dissertations/gh93h1671

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  • Generalized Radial Basis Functions were used to construct networks that learn input-output mappings from given data. They are developed out of a theoretical framework for approximation based on regularization techniques and represent a class of three-layer networks similar to backpropagation networks with one hidden layer. A network using Gaussian base functions was implemented and applied to several domains. It was found to perform very well on the two-spirals problem and on the nettalk task. This paper explains what Generalized Radial Basis Functions are, describes the algorithm, its implementation, and the tests that have been conducted. It draws the conclusion that network. implementations using Generalized Radial Basis Functions are a successful approach for learning from examples.
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  • File scanned at 300 ppi (Monochrome) using ScandAll PRO 1.8.1 on a Fi-6770A in PDF format. CVista PdfCompressor 5.0 was used for pdf compression and textual OCR.
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  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2013-03-21T20:31:41Z (GMT) No. of bitstreams: 1 WettschereckDietrich1991.pdf: 1459968 bytes, checksum: 0af462d7373f7f1d9cce72e8672f5671 (MD5)
  • description.provenance : Approved for entry into archive by Patricia Black(patricia.black@oregonstate.edu) on 2013-03-21T20:57:11Z (GMT) No. of bitstreams: 1 WettschereckDietrich1991.pdf: 1459968 bytes, checksum: 0af462d7373f7f1d9cce72e8672f5671 (MD5)
  • description.provenance : Submitted by Kaylee Patterson (kdpscanner@gmail.com) on 2013-03-21T19:14:11Z No. of bitstreams: 1 WettschereckDietrich1991.pdf: 1459968 bytes, checksum: 0af462d7373f7f1d9cce72e8672f5671 (MD5)
  • description.provenance : Made available in DSpace on 2013-03-21T20:57:11Z (GMT). No. of bitstreams: 1 WettschereckDietrich1991.pdf: 1459968 bytes, checksum: 0af462d7373f7f1d9cce72e8672f5671 (MD5) Previous issue date: 1990-06-27

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