Asynchronous dynamics of random Boolean networks

Craig Gotsman, Eli Shamir, Daniel Lehmann

Research output: Contribution to conferencePaperpeer-review

3 Scopus citations

Abstract

A generalization of neural networks called Boolean networks is considered. Random (n, k)-networks consist of n processors, each connected randomly to k others, computing random k-input Boolean functions. The dynamic behavior of these networks has been studied extensively. The authors examine the asynchronous dynamics of these networks, and prove that convergence to fixpoints is assured for almost all random (n, k)-networks at the limit n → ∞, provided k > log n. The proof of this result lies in random graph theory. They believe it is the first time this branch of mathematics has been used to analyze dynamic behavior of networks.

Original languageEnglish (US)
Pages1-7
Number of pages7
DOIs
StatePublished - 1988
Externally publishedYes

All Science Journal Classification (ASJC) codes

  • Engineering(all)

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