Nonlinear Sciences – Adaptation and Self-Organizing Systems
Scientific paper
1994-06-20
Nonlinear Sciences
Adaptation and Self-Organizing Systems
19 pages, 7 figures(not included) available upon request, postscript file
Scientific paper
We study a modular neuron alternative to the McCulloch-Pitts neuron that arises naturally in analog devices in which the neuron inputs are represented as coherent oscillatory wave signals. Although the modular neuron can compute $XOR$ at the one neuron level, it is still characterized by the same Vapnik-Chervonenkis dimension as the standard neuron. We give the formulas needed for constructing networks using the new neuron and training them using back-propagation. A numerical study of the modular neuron on two data sets is presented, which demonstrates that the new neuron performs at least as well as the standard neuron.
Adler Stepehn L.
Bhanot G. V.
Weckel J. D.
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