Training radial basis neural networks with the extended Kalman filter

DOI10.1016/S0925-2312(01)00611-7zbMath1006.68797OpenAlexW2112492235MaRDI QIDQ1851998

Dan Simon

Publication date: 9 January 2003

Published in: Neurocomputing (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1016/s0925-2312(01)00611-7

zbMATH Keywords

Kalman filterOptimizationTrainingGradient descentRadial basis function (RBF)

Mathematics Subject Classification ID

Learning and adaptive systems in artificial intelligence (68T05) Computing methodologies and applications (68U99)

Related Items (4)

Robust sequential learning of feedforward neural networks in the presence of heavy-tailed noise ⋮ Extended and unscented Kalman filtering based feedforward neural networks for time series prediction ⋮ Using radial basis function networks for function approximation and classification ⋮ A growing and pruning sequential learning algorithm of hyper basis function neural network for function approximation

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