A Theory for Neural Networks with Time Delays. abstract bibtex 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.
@article{noauthor_theory_nodate,
title = {A {Theory} for {Neural} {Networks} with {Time} {Delays}},
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.},
language = {en},
pages = {7}
}
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