Please use this identifier to cite or link to this item: https://doi.org/10.1109/97.511811
Title: Orthogonal least-squares learning algorithm with local adaptation process for the radial basis function networks
Authors: Chng, E.-S. 
Yang, H.H.
Bös, S.
Issue Date: 1996
Citation: Chng, E.-S., Yang, H.H., Bös, S. (1996). Orthogonal least-squares learning algorithm with local adaptation process for the radial basis function networks. IEEE Signal Processing Letters 3 (8) : 253-255. ScholarBank@NUS Repository. https://doi.org/10.1109/97.511811
Abstract: In this letter, we introduce a local adaptation process in the orthogonal least squares (OLS) learning algorithm for the selection of radial basis function (RBF) networks. Using simulation results, we show that the proposed algorithm can find significantly better subset models than the OLS algorithm.
Source Title: IEEE Signal Processing Letters
URI: http://scholarbank.nus.edu.sg/handle/10635/132759
ISSN: 10709908
DOI: 10.1109/97.511811
Appears in Collections:Staff Publications

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