The relevance vector machine technique for channel equalization application
Chen, S., Gunn, S.R. and Harris, C.J. (2001) The relevance vector machine technique for channel equalization application. IEEE Transactions on Neural Networks, 12, (6), 1529-1532.
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Description/Abstract
The recently introduced relevance vector machine (RVM) technique is applied to communication channel equalization. It is demonstrated that the RVM equalizer can closely match the optimal performance of the Bayesian equalizer, with a much sparser kernel representation than that is achievable by the state-of-art support vector machine (SVM) technique.
| Item Type: | Article |
|---|---|
| Additional Information: | submitted for publication in April 2001, accepted June 2001, to appear Nov. 2001 |
| Divisions: | Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Comms, Signal Processing & Control Faculty of Physical Sciences and Engineering > Electronics and Computer Science > Electronic & Software Systems |
| Item ID: | 254483 |
| Date Deposited: | 15 Nov 2001 |
| Last Modified: | 24 May 2013 01:16 |
| Contributors: | Chen, S. (Author) Gunn, S.R. (Author) Harris, C.J. (Author) |
| Date: | November 2001 |
| Additional Information: | submitted for publication in April 2001, accepted June 2001, to appear Nov. 2001 |
| Status: | Published |
| Publisher: | IEEE |
| Further Information: | Google Scholar |
| ISI Citation Count: | 23 |
| URI: | http://eprints.soton.ac.uk/id/eprint/254483 |
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