Memory models of adaptive behavior

Fabio Lorenzo Traversa, Yuriy V. Pershin, Massimiliano Di Ventra

Research output: Contribution to journalArticleResearchpeer-review

30 Citations (Scopus)

Abstract

Adaptive response to varying environment is a common feature of biological organisms. Reproducing such features in electronic systems and circuits is of great importance for a variety of applications. We consider memory models inspired by an intriguing ability of slime molds to both memorize the period of temperature and humidity variations and anticipate the next variations to come, when appropriately trained. Effective circuit models of such behavior are designed using: 1) a set of LC contours with memristive damping and 2) a single memcapacitive system-based adaptive contour with memristive damping. We consider these two approaches in detail by comparing their results and predictions. Finally, possible biological experiments that would discriminate between the models are discussed. In this paper, we also introduce an effective description of certain memory circuit elements. © 2012 IEEE.
Original languageEnglish
Article number6525332
Pages (from-to)1437-1448
JournalIEEE Transactions on Neural Networks and Learning Systems
Volume24
Issue number9
DOIs
Publication statusPublished - 11 Jun 2013

Keywords

  • Adaptive frequency
  • amoeba
  • dynamical systems
  • learning
  • memcapacitive system
  • memory
  • memristor
  • synchronization

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