A new neural network architecture involving either local feedforward global feedforward, and/or local recurrent global feedforward structure is proposed.
It is shown by simulation that networks employing this local-feedback architecture perform better than those with only local feedforward char- acteristics. The ...
A new neural network architecture involving either local feedforward global feedforward, and/or local recurrent global feedforward struc- ture is proposed.
It is shown that the local-recurrent global-feedforward model performs better than the local/local recurrent global feedforward model and the learning rule ...
A new neural network architecture involving either local feedforward global feedforward, and/or local recurrent global feedforward structure is proposed.
FIR and IIR Synapses, a New Neural Network Architecture for Time ...
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A new neural network architecture involving either local feedforward global feedforward, and/or local recurrent global feedforward structure is proposed.
The FIR neural network model was recently proposed for time series prediction and gave good results. However, the learning algorithm used for the FIR ...
The novelty aspect of the architecture consists in replacing the usual scalar values of the output weights with linear FIR or IIR filters transfer functions.
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FIR and IIR Synapses, a New Neural Network Architecture for Time Series Modeling ... Neural Computation (1991) 3 (3): 375–385. Abstract.
In this paper we develop a new learning algorithm for the FIR neural network ... FIR and IIR synapses, a new neural network architecture for time series modeling.