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Neurofuzzy Network Model Construction using Bézier Bernstein Polynomial Functions  (Make Corrections)  
C.J. Harris, X. Hong



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Abstract: | Neurofuzzy modelling systems combine fuzzy logic with quantitative arti cial neural networks via a concept of fuzzi cation by using a fuzzy membership function usually based on B-splines and algebraic operators for inference etc. This paper introduces a new neurofuzzy model construction algorithm using Bezier Bernstein polynomial functions as basis functions. The new network maintains most of the properties of the B-spline expansion based neurofuzzy system, such as nonnegativity of the basis ... (Update)

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BibTeX entry:   (Update)

@misc{ harris-neurofuzzy,
  author = "C.J. Harris and X. Hong",
  title = "Neurofuzzy Network Model Construction using Bézier Bernstein Polynomial
    Functions",
  url = "citeseer.ist.psu.edu/415991.html" }
Citations (may not include all citations):
474   Curves and Surfaces for Computer-aided Geometric Design: a P.. (context) - Farin - 1993
101   Adaptive Filtering Prediction and Control (context) - Goodwin, Sin - 1984
53   Adaptive Fuzzy Systems and Control: design and stability ana.. (context) - Wang - 1994
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