On reliable computation with formal neurons

Author

Venkatesh, Santosh S. ; Psaltis, Demetri

Author_Institution

Moore Sch. of Electr. Eng., Pennsylvania Univ., Philadelphia, PA, USA

Volume

14

Issue

1

fYear

1992

fDate

1/1/1992 12:00:00 AM

Firstpage

87

Lastpage

91

Abstract

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 εm decision errors is allowed, with 0⩽ε<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

Keywords

neural nets; protocols; computing capabilities; decision errors; error tolerance; exhaustive error protocol; formal McCulloch-Pitts neurons; neural nets; random error protocol; Biological system modeling; Biology computing; Boolean functions; Computer errors; Computer networks; Fault tolerance; Neurons; Pattern recognition; Protocols; Reliability theory;

fLanguage

English

Journal_Title

Pattern Analysis and Machine Intelligence, IEEE Transactions on

Publisher

ieee

ISSN

0162-8828

Type

jour

DOI

10.1109/34.107015

Filename

107015