Abstract
The three-dimensional (3D) model of a feedforward neural network (NN) based on so called N-hypercube topology is proposed. The N-hypercube is different from the classical hypercube used in communication theory, and in Boolean algebra. This new structure has been created based on a novel algorithm for embedding a binary decision tree and binary decision diagram into a N-hypercube. It is shown that A-hypercube topology is a reasonable solution to implement NN of threshold gates, in particular, on the single-electron devices. The 3D design methodology of feedforward NN is oriented to technology mapping to nanodevices. Results of extensive experimental study of feedforward networks consisting of over 3500 N-hypercubes are presented.
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Shmerko, V.P., Yanushkevich, S.N. (2004). Three-Dimensional Feedforward Neural Networks and Their Realization by Nano-Devices. In: Artificial Intelligence in Logic Design. Artificial Intelligence in Logic Design, vol 766. Springer, Dordrecht. https://doi.org/10.1007/978-1-4020-2075-9_10
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DOI: https://doi.org/10.1007/978-1-4020-2075-9_10
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