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Resistive random access memories (RRAMs) constitute a class of memristive devices particularly appealing for bio-inspired computing schemes. In particular, the possibility of achieving analog control of the electrical conductivity of RRAM devices can be exploited to mimic the behaviour of biological synapses in neuromorphic systems. With a view to neuromorphic computing applications, it turns out to be crucial to guarantee some features, among which a detailed device characterization, a mathematical modelling comprehensive of all the key features of the device both in quasi-static and dynamic conditions, a description of the variability due to the inherently stochasticity of the processes involved in the switching transitions. In this paper, starting from experimental data, we provide a modelling and simulation framework to reproduce the operative analog behaviour of HfOx-based RRAM devices under train of …
IOP Publishing
Publication date: 
25 May 2022

Francesco Vaccaro, Stefano Brivio, Simona Perotto, Aurelio Giancarlo Mauri, Sabina Spiga

Biblio References: 
Neuromorphic Computing and Engineering