Prediction of Chaotic Time-Series with a Resource-Allocating RBF Network

Authors:
Roman Rosipal;Miloš Koska;Igor Farkaš
Affiliations:
Institute of Measurement Science, Slovak Academy of Sciences, Dúbravská cesta 9, 842 19 Bratislava, Slovakia;Institute of Measurement Science, Slovak Academy of Sciences, Dúbravská cesta 9, 842 19 Bratislava, Slovakia;Institute of Measurement Science, Slovak Academy of Sciences, Dúbravská cesta 9, 842 19 Bratislava, Slovakia
Venue:
Neural Processing Letters
Year:
1998

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Abstract

One of the main problems associated with artificial neural networkson-line learning methods is the estimation of model order. In this paper,we report about a new approach to constructing a resource-allocating radialbasis function network exploiting weights adaptation using recursiveleast-squares technique based on Givens QR decomposition. Further, we studythe performance of pruning strategy we introduced to obtain the sameprediction accuracy of the network with lower model order. The proposedmethods were tested on the task of Mackey-Glass time-series prediction.Order of resulting networks and their prediction performance were superiorto those previously reported by Platt [12].