Short-term memory in orthogonal neural networks

Olivia L. White, Daniel D. Lee, Haim Sompolinsky

Research output: Contribution to journalArticlepeer-review

118 Scopus citations

Abstract

We study the ability of linear recurrent networks obeying discrete time dynamics to store long temporal sequences that are retrievable from the instantaneous state of the network. We calculate this temporal memory capacity for both distributed shift register and random orthogonal connectivity matrices. We show that the memory capacity of these networks scales with system size.

Original languageEnglish
Pages (from-to)148102
Number of pages1
JournalPhysical Review Letters
Volume92
Issue number14
StatePublished - 9 Apr 2004
Externally publishedYes

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