A generalized growing and pruning RBF (GGAP-RBF) neural network for function approximation

IEEE Transactions on Neural Networks

Volumn 16, Issue 1, 2005, Pages 57-67

  Huang, Guang Bin ^a   Saratchandran, P ^a   Sundararajan, Narasimhan ^a  

^a NANYANG TECHNOLOGICAL UNIVERSITY   (Singapore)

Author keywords

Growing; Neuron's significance; Pruning; Radial basis networks; Sequential learning

Indexed keywords

APPROXIMATION THEORY; COMPUTER SIMULATION; LEARNING ALGORITHMS; LEARNING SYSTEMS; OPTIMIZATION; PROBABILITY DENSITY FUNCTION; REGRESSION ANALYSIS; SEQUENTIAL MACHINES; STATISTICAL METHODS;

ARBITRARY SAMPLING DENSITY FUNCTION; GROWING RADIAL BASIS FUNCTION; LEARNING ACCURACY; PRUNING RADIAL BASIS FUNCTION; SEQUENTIAL LEARNING ALGORITHM;

RADIAL BASIS FUNCTION NETWORKS;

ALGORITHM; ARTICLE; ARTIFICIAL INTELLIGENCE; ARTIFICIAL NEURAL NETWORK; CLUSTER ANALYSIS; COMPUTER ANALYSIS; EVALUATION; MATHEMATICAL COMPUTING;

ALGORITHMS; ARTIFICIAL INTELLIGENCE; CLUSTER ANALYSIS; COMPUTING METHODOLOGIES; NEURAL NETWORKS (COMPUTER); NUMERICAL ANALYSIS, COMPUTER-ASSISTED;

EID: 13844256702     PISSN: 10459227     EISSN: None     Source Type: Journal    
DOI: 10.1109/TNN.2004.836241     Document Type: Article

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