Adaptive Neuromorphic Architecture (ANA)

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Frank Zhigang Wang - , University of Kent (Autor:in)
  • Leon O. Chua - , University of Kent, University of California at Berkeley (Autor:in)
  • Xiao Yang - , University of Kent (Autor:in)
  • Na Helian - , University of Hertfordshire (Autor:in)
  • Ronald Tetzlaff - , Professur für Grundlagen der Elektrotechnik (GE) (Autor:in)
  • Torsten Schmidt - , Technische Universität Dresden (Autor:in)
  • Caroline Li - , University of Kent (Autor:in)
  • Jose Manuel Garcia Carrasco - , University of Murcia (Autor:in)
  • Wanlong Chen - , University of Kent (Autor:in)
  • Dominique Chu - , University of Kent (Autor:in)

Abstract

We designed Adaptive Neuromorphic Architecture (ANA) that self-adjusts its inherent parameters (for instance, the resonant frequency) naturally following the stimuli frequency. Such an architecture is required for brain-like engineered systems because some parameters of the stimuli (for instance, the stimuli frequency) are not known in advance. Such adaptivity comes from a circuit element with memory, namely mem-inductor or mem-capacitor (memristor's sisters), which is history-dependent in its behavior. As a hardware model of biological systems, ANA can be used to adaptively reproduce the observed biological phenomena in amoebae.

Details

OriginalspracheEnglisch
Seiten (von - bis)111-116
Seitenumfang6
FachzeitschriftNeural Networks
Jahrgang45
PublikationsstatusVeröffentlicht - 13 März 2013
Peer-Review-StatusJa

Externe IDs

PubMed 23541822
ORCID /0000-0001-7436-0103/work/142240347

Schlagworte

Schlagwörter

  • Brain-like engineered systems, Memristors, Neural circuits, Neuromorphic engineering

Bibliotheksschlagworte