A pragmatic gaze on stochastic resonance based variability tolerant memristance enhancement
Vasileios Ntinas (Democritus University of Thrace, Universitat Politecnica de Catalunya)
A Rubio (Universitat Politecnica de Catalunya)
Georgios Ch Sirakoulis (Democritus University of Thrace)
Sorin D. Cotofana (TU Delft - Computer Engineering)
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Abstract
Stochastic Resonance (SR) is a nonlinear system specific phenomenon, which was demonstrated to lead to system unexpected (counter-intuitive) performance improvements under certain noise conditions. Memristor, on the other hand, is a fundamentally nonlinear circuit element, thus susceptible to benefit from SR, which recently came in the spotlight of the emerging technologies potential candidates. However, at this time, the variability exhibited by manufactured memristor devices within the same array constitutes the main hurdle in the road towards the commercialisation of memristor-based memories and/or computing units. Thus, in this paper, memristor SR effects are explored, assuming various memristor models, and SR-based memristance range enhancement, tolerant to device-to-device variability, is demonstrated. Our experiments reveal that SR can induce significant RMAX/RMIN ratio increase under up to 60% variability, getting as high as 3.4× for 29 dBm noise power.
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