Please use this identifier to cite or link to this item:
|Title:||Orthogonal least-squares learning algorithm with local adaptation process for the radial basis function networks|
|Authors:||Chng, E.-S. |
|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|
|Appears in Collections:||Staff Publications|
Show full item record
Files in This Item:
There are no files associated with this item.
checked on Nov 11, 2018
WEB OF SCIENCETM
checked on Oct 17, 2018
checked on Nov 15, 2018
Items in DSpace are protected by copyright, with all rights reserved, unless otherwise indicated.