A New Approach Using Temporal Radial Basis Function in Chronological Series

In this paper, we present an extended form of the radial basis function network called temporal- radial basisfunction network. This extended network is used in decision rules and classification in spatio-temporal domain applicationslike speech recognition, economic fluctuations, seismic measurements and robotics applications. We found that such a networkcomplies, with a relative ease, to constraints such as capacity of universal approximation, sensibility of node, localgeneralisation in receptive field, etc. For an optimal solution based on a probabilistic approach with a minimum ofcomplexity, we developped two temporal radial basis function models. Application to the problem of Mackey-Glass timeseries, it has revealed that temporal radial basis function models are very promising, compared to traditional networks