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On Reliable Computation With Formal Neurons
January 1992 (vol. 14 no. 1)
pp. 87-91

The authors investigate the computing capabilities of formal McCulloch-Pitts neurons when errors are permitted in decisions. They assume that m decisions are to be made on a randomly specified m set of points in n space and that an error tolerance of epsilon m decision errors is allowed, with 0>or= epsilon >1/2. The authors are interested in how large an m can be selected such that the neuron makes reliable decisions within the prescribed error tolerance. Formal results for two protocols for error-tolerance-a random error protocol and an exhaustive error protocol-are obtained. The results demonstrate that a formal neuron has a computational capacity that is linear in n and that this rate of capacity growth persists even when errors are tolerated in the decisions.

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Index Terms:
neural nets; computing capabilities; formal McCulloch-Pitts neurons; decision errors; error tolerance; random error protocol; exhaustive error protocol; neural nets; protocols
Citation:
S.S. Venkatesh, D. Psaltis, "On Reliable Computation With Formal Neurons," IEEE Transactions on Pattern Analysis and Machine Intelligence, vol. 14, no. 1, pp. 87-91, Jan. 1992, doi:10.1109/34.107015
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