Noisy time series prediction using M-estimator based robust radial basis function neural networks with growing and pruning techniques

Expert Systems with Applications

Volumn 36, Issue 3 PART 1, 2009, Pages 4717-4724

  Lee, Chien Cheng ^a   Chiang, Yu Chun ^a   Shih, Cheng Yuan ^a   Tsai, Chun Li ^b  

^a YUAN ZE UNIVERSITY   (Taiwan)

^b NATIONAL CHENG KUNG UNIVERSITY   (Taiwan)

Author keywords

Growing and pruning (GAP); Least mean square (LMS); M estimator; Radial basis function (RBF); Time series

Indexed keywords

ADDITIVE NOISE; FORECASTING; FUNCTIONS; LEARNING ALGORITHMS; PLANNING; SIGNAL PROCESSING; TIME SERIES;

GROWING AND PRUNING; LEAST MEAN SQUARE (LMS); M-ESTIMATORS; NON-LINEAR TIME-SERIES MODELS; PREDICTION PROBLEM; RADIAL BASIS FUNCTION NEURAL NETWORKS; RADIAL BASIS FUNCTION(RBF); TIME SERIES PREDICTION;

RADIAL BASIS FUNCTION NETWORKS;

EID: 58349093296     PISSN: 09574174     EISSN: None     Source Type: Journal    
DOI: 10.1016/j.eswa.2008.06.017     Document Type: Article

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