Improving the prediction capability of radial basis function networks

Industrial and Engineering Chemistry Research

Volumn 37, Issue 10, 1998, Pages 3956-3970

  Gurumoorthy, Anand ^a   Kosanovich, Karlene A ^a  

^a University of South Carolina   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

CHEMICAL INDUSTRY; FUNCTIONS; INTERPOLATION; LEAST SQUARES APPROXIMATIONS; NEURAL NETWORKS;

OBJECTIVE FUNCTION; RADIAL BASIS FUNCTION NETWORKS;

PROCESS CONTROL;

EID: 0032180257     PISSN: 08885885     EISSN: None     Source Type: Journal    
DOI: 10.1021/ie980278o     Document Type: Article

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37. 1 and its limit points are the set Y.
38. 1 has a convergent subsequence whose limit is an element of Y. Every compact set is closed and bounded.
39. A complete inner product space.
40. 24