Multiple-Model Approach to Non-Linear Kernel- Based Adaptive Filtering
Dodd, T.J., Mitchinson, B and Harrison, R.F.
(2003)
Multiple-Model Approach to Non-Linear Kernel- Based Adaptive Filtering.
Research Report.
ACSE Report 830
.
Department of Control Engineering, University of Sheffield, Mappin Street, Sheffield
Abstract
Kernel methods now provide standard tools for the solution of function approximation and pattern classification problems. However, it is typically assumed that all data are available for training. More recently, various approaches have been proposed for extending kernel methods to sequential problems whereby the model is updated as each new data point arrives. Whilst these approaches have proven successful in estimating the basic parameters, the problem of estimating the hyperparameters , which determine the overall model behaviour, remains essentially unsolved.
Metadata
Item Type:
Monograph
Authors/Creators:
Dodd, T.J.
Mitchinson, B
Harrison, R.F.
Copyright, Publisher and Additional Information:
The Department of Automatic Control and Systems Engineering research reports offer a forum for the research output of the academic staff and research students of the Department at the University of Sheffield. Papers are reviewed for quality and presentation by a departmental editor. However, the contents and opinions expressed remain the responsibility of the authors. Some papers in the series may have been subsequently published elsewhere and you are advised to cite the later published version in these instances.
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