title: A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.
abstract: Resistive (or memristive) switching devices based on metal oxides find applications in memory, logic and neuromorphic computing systems. Their small area, low power operation, and high functionality meet the challenges of brain-inspired computing aiming at achieving a huge density of active connections (synapses) with low operation power. This work presents a new artificial synapse scheme, consisting of a memristive switch connected to 2 transistors responsible for gating the communication and learning operations. Spike timing dependent plasticity (STDP) is achieved through appropriate shaping of the pre-synaptic and the post synaptic spikes. Experiments with integrated artificial synapses demonstrate STDP with stochastic behavior due to (i) the natural variability of set/reset processes in the nanoscale switch, and (ii) the different response of the switch to a given stimulus depending on the initial state. Experimental results are confirmed by model-based simulations of the memristive switching. Finally, system-level simulations of a 2-layer neural network and a simplified STDP model show random learning and recognition of patterns.
authors: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano and IU.NET Milano, Italy.
authors: Zhongqiang
authors: Z
authors: Wang
authors: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano and IU.NET Milano, Italy.
authors: Stefano
authors: S
authors: Ambrogio
authors: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano and IU.NET Milano, Italy.
authors: Simone
authors: S
authors: Balatti
authors: Dipartimento di Elettronica, Informazione e Bioingegneria, Politecnico di Milano and IU.NET Milano, Italy.
authors: Daniele
authors: D
authors: Ielmini
keywords: cognitive computing; memristor; neural network; neuromorphic circuits; pattern recognition; spike timing dependent plasticity
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