Abstract
Radial basis function and Volterra series predictors are examined with a view to reducing their complexity while maintaining prediction performance. A geometrical interpretation of the problem is presented. This interpretation indicates that while a multiplicity of choices of reduced state predictor exist, some may be better than others in terms of the numerical conditioning of the solution.
Original language | English |
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Publication status | Published - 22 Nov 1991 |
Event | IEE Colloquium on Adaptive Filtering, Non-Linear Dynamics and Neural Networks - London, United Kingdom Duration: 22 Nov 1991 → 22 Nov 1991 |
Conference
Conference | IEE Colloquium on Adaptive Filtering, Non-Linear Dynamics and Neural Networks |
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Country/Territory | United Kingdom |
City | London |
Period | 22/11/91 → 22/11/91 |