DocumentCode :
3493473
Title :
An adaptive support vector regression filter: A signal detection application
Author :
Rosipal, Roman ; Gorilami, M.
Author_Institution :
Comput. Intelligence Res. Unit, Univ. of Paisley, UK
Volume :
2
fYear :
1999
fDate :
1999
Firstpage :
603
Abstract :
A new method for the construction of nonlinear adaptive filters called adaptive support vector regression is introduced for signal detection in noisy environments. A modification of support vector regression for online learning is motivated by the chunking approach and is based on repeated retraining of the filter parameters without the loss of former estimates. Performance of the proposed method was found superior to the method using a resource-allocating RBF network with Givens QR decomposition and pruning
Keywords :
neural nets; adaptive support vector regression filter; filter parameters; noisy environments; nonlinear adaptive filter construction; online learning; signal detection;
fLanguage :
English
Publisher :
iet
Conference_Titel :
Artificial Neural Networks, 1999. ICANN 99. Ninth International Conference on (Conf. Publ. No. 470)
Conference_Location :
Edinburgh
ISSN :
0537-9989
Print_ISBN :
0-85296-721-7
Type :
conf
DOI :
10.1049/cp:19991176
Filename :
817997
Link To Document :
بازگشت