Learning algorithm for nonlinear support vector machines suited for digital VLSI

Authors
Anguita, D Boni, A Ridella, S
Citation
D. Anguita et al., Learning algorithm for nonlinear support vector machines suited for digital VLSI, ELECTR LETT, 35(16), 1999, pp. 1349-1350
Citations number
6
Categorie Soggetti
Eletrical & Eletronics Engineeing
Journal title
ELECTRONICS LETTERS
ISSN journal
00135194 → ACNP
Volume
35
Issue
16
Year of publication
1999
Pages
1349 - 1350
Database
ISI
SICI code
0013-5194(19990805)35:16<1349:LAFNSV>2.0.ZU;2-V
Abstract
A learning algorithm for radial basis function support vector machines (RBF -SVMs) that can be easily implemented in digital VLSI is proposed. It is sh own that, as opposed to traditional artificial neural networks, learning in SVMs is very robust with respect to quantisation effects deriving from the finite precision of computations.