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Title: Delayed switching applied to memristor neural networks

Journal Article · · Journal of Applied Physics
DOI:https://doi.org/10.1063/1.3672409· OSTI ID:22038931
; ;  [1];  [2];  [3];  [4];  [5]
  1. Future Computing Group, School of Computing, University of Kent, Canterbury (United Kingdom)
  2. School of Computer Science, University of Hertfordshire, Hatfield (United Kingdom)
  3. Xyratex, Havant (United Kingdom)
  4. Department of Computing, Imperial College, London (United Kingdom)
  5. CERN, Geneva (Switzerland)

Magnetic flux and electric charge are linked in a memristor. We reported recently that a memristor has a peculiar effect in which the switching takes place with a time delay because a memristor possesses a certain inertia. This effect was named the ''delayed switching effect.'' In this work, we elaborate on the importance of delayed switching in a brain-like computer using memristor neural networks. The effect is used to control the switching of a memristor synapse between two neurons that fire together (the Hebbian rule). A theoretical formula is found, and the design is verified by a simulation. We have also built an experimental setup consisting of electronic memristive synapses and electronic neurons.

OSTI ID:
22038931
Journal Information:
Journal of Applied Physics, Vol. 111, Issue 7; Conference: 55. annual conference on magnetism and magnetic materials, Atlanta, GA (United States), 14-18 Nov 2010; Other Information: (c) 2012 American Institute of Physics; Country of input: International Atomic Energy Agency (IAEA); ISSN 0021-8979
Country of Publication:
United States
Language:
English