DocumentCode
2131704
Title
High-dimensional approximation using an associative memory network
Author
Brown, Michael ; Harris, Chris J.
Volume
2
fYear
1994
fDate
21-24 March 1994
Firstpage
1458
Abstract
In this paper a framework has been outlined for an automatic approximation scheme, based on adaptive spline modelling of observational data, suitable for application to high-dimensional modelling and control problems. The points to be considered include: selecting the basis aij, model construction, the learning algorithm to optimise the linear coefficients and the criteria for model structure evaluation.
Keywords
approximation theory; content-addressable storage; identification; learning (artificial intelligence); neural nets; splines (mathematics); adaptive spline modelling; associative memory network; automatic approximation; high-dimensional modelling; identification; learning algorithm; linear coefficients; model construction; model structure evaluation; observational data;
fLanguage
English
Publisher
iet
Conference_Titel
Control, 1994. Control '94. International Conference on
Conference_Location
Coventry, UK
Print_ISBN
0-85296-610-5
Type
conf
DOI
10.1049/cp:19940352
Filename
327270
Link To Document