Emergent spiking in non-ideal memristor networks

Gale, E., de Lacy Costello, B. and Adamatzky, A. (2014) Emergent spiking in non-ideal memristor networks. Microelectronics Journal, 45 (11). pp. 1401-1415. ISSN 0026-2692 Available from: http://eprints.uwe.ac.uk/26991

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Publisher's URL: http://dx.doi.org/10.1016/j.mejo.2014.06.008


Memristors have uses as artificial synapses and perform well in this role in simulations with artificial spiking neurons. Our experiments show that memristor networks natively spike and can exhibit emergent oscillations and bursting spikes. Networks of near-ideal memristors exhibit behaviour similar to a single memristor and combine in circuits like resistors do. Spiking is more likely when filamentary memristors are used or the circuits have a higher degree of compositional complexity (i.e. a larger number of anti-series or anti-parallel interactions). 3-memristor circuits with the same memristor polarity (low compositional complexity) are stabilised and do not show spiking behaviour. 3-memristor circuits with anti-series and/or anti-parallel compositions show richer and more complex dynamics than 2-memristor spiking circuits. We show that the complexity of these dynamics can be quantified by calculating (using partial auto-correlation functions) the minimum order auto-regression function that could fit it. We propose that these oscillations and spikes may have similar phenomena to brainwaves and neural spike trains and suggest that these behaviours can be used to perform neuromorphic computation.

Item Type:Article
Uncontrolled Keywords:memristor, ReRAM, network, emergence, spiking, neuromorphic, computation
Faculty/Department:Faculty of Environment and Technology > Department of Computer Science and Creative Technologies
ID Code:26991
Deposited By: Professor A. Adamatzky
Deposited On:25 Sep 2015 10:18
Last Modified:18 Dec 2016 07:09

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