Analysis on bidirectional associative memories with multiplicative weight noise

Chi Sing Leung, Pui Fai Sum, Tien-Tsin Wong

Research output: Chapter in Book/Report/Conference proceedingConference PaperResearchpeer-review

Abstract

In neural networks, network faults can be exhibited in different forms, such as node fault and weight fault. One kind of weight faults is due to the hardware or software precision. This kind of weight faults can be modelled as multiplicative weight noise. This paper analyzes the capacity of a bidirectional associative memory (BAM) affected by multiplicative weight noise. Assuming that weights are corrupted by multiplicative noise, we study how many number of pattern pairs can be stored as fixed points. Since capacity is not meaningful without considering the error correction capability, we also present the capacity of a BAM with multiplicative noise when there are some errors in the input pattern. Simulation results have been carried out to confirm our derivations.

Original languageEnglish
Title of host publicationNeural Information Processing - 14th International Conference, ICONIP 2007, Revised Selected Papers
PublisherSpringer
Pages289-298
Number of pages10
EditionPART 1
ISBN (Print)3540691545, 9783540691549
DOIs
Publication statusPublished - 2008
Externally publishedYes
EventInternational Conference on Neural Information Processing 2007 - Kitakyushu, Japan
Duration: 13 Nov 200716 Nov 2007
Conference number: 14th
https://link.springer.com/book/10.1007/978-3-540-69158-7 (Proceedings)

Publication series

NameLecture Notes in Computer Science
PublisherSpringer
NumberPART 1
Volume4984
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

ConferenceInternational Conference on Neural Information Processing 2007
Abbreviated title ICONIP 2007
Country/TerritoryJapan
CityKitakyushu
Period13/11/0716/11/07
Internet address

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