A new hybrid recurrent neural network
Xiqun Lu, Chun Chen · 2003
A new hybrid type of recurrent neural network is reported in this paper. Unlike those of the general recurrent neural networks, the activation functions of its hidden neurons are chosen to be Gaussian functions. The performance of this hybrid network for nonlinear nonstationary time series prediction is tested. Two popular time series produced by the Mackey-Glass equation and the Lorenz equation are used in the simulation.