Two-layered oscillatory neural networks with analog feedforward majority gate for image edge detection application

Madeleine Abernot, Corentin Delacour, Ahmet Suna, J. Marty Gregg, Siegfried Karg, Aida Todri-Sanial

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

The increasing volume of smart edge devices, like smart cameras, and the growing amount of data to treat incited the development of light edge Artificial Intelligence (AI) solutions with neuromorphic computing. Oscillatory Neural Network (ONN) is a promising neuromorphic computing approach which uses networks of coupled oscillators, and their inherent parallel synchronization to compute. Also, ONN phase computing allows to limit voltage amplitude and reduce power consumption. Low-power, fast, and parallel computation properties make ONN attractive for edge AI. In state-of-the-art, ONN is built with a fully-connected architecture, with coupling defined from unsupervised learning to perform auto-associative memory tasks, like with Hopfield Networks. However, to allow ONN to solve beyond associative memory applications, there is a need to explore further ONN architectures. In this work, we propose a novel architecture of cascaded analog fully-connected ONNs interconnected with an analog feedforward majority gate layer. In particular, we show this architecture can solve image edge detection task using two fully-connected ONN layers. This is, to our best knowledge, a first analog-based solution to cascade two fully-connected ONNs.

Original languageEnglish
Title of host publicationISCAS 2023 - 56th IEEE International Symposium on Circuits and Systems, Proceedings
PublisherInstitute of Electrical and Electronics Engineers Inc.
Number of pages5
ISBN (Electronic)9781665451093
ISBN (Print)9781665451109
DOIs
Publication statusPublished - 21 Jul 2023
Event56th IEEE International Symposium on Circuits and Systems, ISCAS 2023 - Monterey, United States
Duration: 21 May 202325 May 2023

Publication series

NameProceedings - IEEE International Symposium on Circuits and Systems
Volume2023-May
ISSN (Print)0271-4310
ISSN (Electronic)2158-1525

Conference

Conference56th IEEE International Symposium on Circuits and Systems, ISCAS 2023
Country/TerritoryUnited States
CityMonterey
Period21/05/202325/05/2023

Keywords

  • Feedforward
  • Image Edge Detection
  • Majority Gate
  • Oscillatory Neural Networks

ASJC Scopus subject areas

  • Electrical and Electronic Engineering

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