Topological Properties of Hypercubes
IEEE Transactions on Computers
Depth-Size Tradeoffs for Neural Computation
IEEE Transactions on Computers - Special issue on artificial neural networks
Spatial tessellations: concepts and applications of Voronoi diagrams
Spatial tessellations: concepts and applications of Voronoi diagrams
Incomplete hypercubes: embeddings of tree-related networks
Journal of Parallel and Distributed Computing
Mathematical Modeling: Design of Complex Computer Systems
Mathematical Modeling: Design of Complex Computer Systems
Handbook of Neural Computation
Handbook of Neural Computation
Ordered binary decision diagrams
Logic Synthesis and Verification
Silicon Single-Electron Devices and Their Applications
ISMVL '00 Proceedings of the 30th IEEE International Symposium on Multiple-Valued Logic
Representation of Logical Circuits by Linear Decision Diagrams with Extension to Nanostructures
Automation and Remote Control
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The three-dimensional (3D) model of a feedforward neural network(NN) based on so called N-hypercube topology isproposed. The N-hypercube is different from theclassical hypercube used in communication theory, and in Booleanalgebra. This new structure has been created based on a novelalgorithm for embedding a binary decision tree and binary decisiondiagram into a N-hypercube. It is shown thatN-hypercube topology is a reasonable solution toimplement NN of threshold gates, in particular, on thesingle-electron devices. The 3D design methodology of feedforwardNN is oriented to technology mapping to nanodevices. Results ofextensive experimental study of feedforward networks consistingof over 3500 N-hypercubes are presented.