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An adaptive support vector regression filter: A signal detection application

Rosipal, R; Girolami, M; (1999) An adaptive support vector regression filter: A signal detection application. In: NINTH INTERNATIONAL CONFERENCE ON ARTIFICIAL NEURAL NETWORKS (ICANN99), VOLS 1 AND 2. (pp. 603 - 607). INST ELECTRICAL ENGINEERS INSPEC INC

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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 [8].

Type: Proceedings paper
Title: An adaptive support vector regression filter: A signal detection application
Event: 9th International Conference on Artificial Neural Networks (ICANN99)
Location: UNIV EDINBURGH, EDINBURGH, SCOTLAND
Dates: 1999-09-07 - 1999-09-10
ISBN: 0-85296-721-7
UCL classification: UCL > School of BEAMS > Faculty of Maths and Physical Sciences > Statistical Science
URI: http://discovery.ucl.ac.uk/id/eprint/1339668
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