Can dynamic neural filters produce pseudo-random sequences?

Yishai M. Elyada, David Horn

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

Abstract

Dynamic neural filters (DNFs) are recurrent networks of binary neurons. Under proper conditions of their synaptic matrix they are known to generate exponentially large cycles. We show that choosing the synaptic matrix to be a random orthogonal one, the average cycle length becomes close to that of a random map. We then proceed to investigate the inversion problem and argue that such a DNF could be used to construct a pseudo-random generator. Subjecting this generator's output to a battery of tests we demonstrate that the sequences it generates may indeed be regarded as pseudo-random.

Original languageEnglish
Title of host publicationLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Pages211-216
Number of pages6
DOIs
StatePublished - 2005
Event15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005 - Warsaw, Poland
Duration: 11 Sep 200515 Sep 2005

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume3696 LNCS
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference15th International Conference on Artificial Neural Networks: Biological Inspirations - ICANN 2005
Country/TerritoryPoland
CityWarsaw
Period11/09/0515/09/05

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