A 2-transistor/1-resistor artificial synapse capable of communication and stochastic learning in neuromorphic systems.

Zhongqiang Wang,Simone Balatti,Stefano Ambrogio,Daniele Ielmini

doi:10.3389/fnins.2014.00438

Zhongqiang Wang, Simone Balatti + Show 2 more

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https://doi.org/10.3389/fnins.2014.00438

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Journal: Frontiers in Neuroscience	Publication Date: Jan 15, 2015
Citations: 84	License type: cc-by

Affiliation: Politecnico di Milano

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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.

Highlights

Brain-inspired computing is among the top challenges of the today’s information and communication technology
A memristor naturally satisfies the requisites for electrically-tunable conductance, serving as a connection for communication between a pre-synaptic neuron (PRE) and a post-synaptic neuron (POST), and responsive to the individual spikes fed from both neurons
long-term depression (LTD) can be seen at positive delays, which is due to a sequence of reset and set events in the memristor during the negative and positive regions of the top electrode (TE) pulse, respectively

Summary

Introduction

Brain-inspired computing is among the top challenges of the today’s information and communication technology. 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.

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