DocumentCode
2835843
Title
Sequentially adaptive neural networks
Author
Kadirkamanathan, V. ; Fallside, F.
Author_Institution
Dept. of Eng., Cambridge Univ., UK
fYear
1989
fDate
22-24 Nov 1989
Firstpage
132
Lastpage
135
Abstract
A sequential adaptation scheme for neural networks is proposed. The scheme is formulated as equality constrained optimization tasks. The approach taken in developing the scheme is based on the geometric point of view of pattern recognition and on methods of surface interpolation. The set of training equations for the radial basis function network of Gaussian nodes is developed, and an experiment on its classification performance is carried out
Keywords
interpolation; neural nets; optimisation; pattern recognition; Gaussian nodes; classification performance; equality constrained optimization; pattern recognition; radial basis function network; surface interpolation; training equations; Adaptive systems; Biological neural networks; Constraint optimization; Equations; Interpolation; Kernel; Multilayer perceptrons; Neural networks; Pattern recognition; Training data;
fLanguage
English
Publisher
ieee
Conference_Titel
TENCON '89. Fourth IEEE Region 10 International Conference
Conference_Location
Bombay
Type
conf
DOI
10.1109/TENCON.1989.176912
Filename
176912
Link To Document