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Memristor-Based Edge Detection for Spike Encoded Pixels

Mannion, DJ; Mehonic, A; Ng, WH; Kenyon, AJ; (2020) Memristor-Based Edge Detection for Spike Encoded Pixels. Frontiers in Neuroscience , 13 (1386) 10.3389/fnins.2019.01386. Green open access

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Abstract

Memristors have many uses in machine learning and neuromorphic hardware. From memory elements in dot product engines to replicating both synapse and neuron wall behaviors, the memristor has proved a versatile component. Here we demonstrate an analog mode of operation observed in our silicon oxide memristors and apply this to the problem of edge detection. We demonstrate how a potential divider exploiting this analog behavior can prove a scalable solution to edge detection. We confirm its behavior experimentally and simulate its performance on a standard testbench. We show good performance comparable to existing memristor based work with a benchmark score of 0.465 on the BSDS500 dataset, while simultaneously maintaining a lower component count.

Type: Article
Title: Memristor-Based Edge Detection for Spike Encoded Pixels
Open access status: An open access version is available from UCL Discovery
DOI: 10.3389/fnins.2019.01386
Publisher version: http://dx.doi.org/10.3389/fnins.2019.01386
Language: English
Additional information: © 2020 Mannion, Mehonic, Ng and Kenyon. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
Keywords: memristor, edge detection, computer vision, spiking neural networks, neuromorphic computing
UCL classification: UCL
UCL > Provost and Vice Provost Offices
UCL > Provost and Vice Provost Offices > UCL BEAMS
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Dept of Electronic and Electrical Eng
UCL > Provost and Vice Provost Offices > UCL BEAMS > Faculty of Engineering Science > Engineering Science Faculty Office
URI: https://discovery.ucl.ac.uk/id/eprint/10089867
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