A Theory for Neural Networks with Time Delays
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TL;DR
This model, the gamma neural model, is as general as a convolution delay model with arbitrary weight kernels w(t) and it is shown that the gamma model can be formulated as a (partially prewired) additive model.
Abstract
We present a new neural network model for processing of temporal patterns. This model, the gamma neural model, is as general as a convolution delay model with arbitrary weight kernels w(t). We show that the gamma model can be formulated as a (partially prewired) additive model. A temporal hebbian learning rule is derived and we establish links to related existing models for temporal processing.