Synthesis of multiple-valued logic functions by neural networks.

Alioune. Ngom
The issue we address in this thesis is that of implementing multiple-valued logic systems by neural networks. In particular we discuss models of multiple-valued logic neurons (and neural networks) and how such models might be used to learn or compute multiple-valued logic functions. Analog computers are inherently inaccurate due to imperfections in fabrication and fluctuations in operating temperatures. The classical solution to this problem uses extra hardware to enforce discrete behavior. However, the brain appears...
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