October 19, 2019 Conference paper Open Access

Douthwaite, Matthew; Garcıa-Redondo, Fernando; Georgiou, Pantelis; Das, Shidhartha

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{
  "inLanguage": {
    "alternateName": "eng", 
    "@type": "Language", 
    "name": "English"
  }, 
  "description": "<p>Flexible electronics is becoming more prevalent in a wide range of applications, particularly wearable biomedical<br>\ndevices. These devices would greatly benefit from in-built intelligence allowing them to process data and identify features,<br>\nin order to reduce transmission and power requirements. In this work, we present a novel time-domain multiply-accumulate<br>\n(MAC) engine architecture that can act as the basic block of an artificial analogue neural network. The design does not require<br>\nanalogue voltage buffers, making them easier to realise in flexible technologies and consumes less power than conventional methods. The research could be used in future to construct a low power classifier for a low cost, flexible wearable biomedical sensor.</p>", 
  "license": "https://creativecommons.org/licenses/by/4.0/legalcode", 
  "creator": [
    {
      "affiliation": "Imperial College London", 
      "@type": "Person", 
      "name": "Douthwaite, Matthew"
    }, 
    {
      "affiliation": "ARM Research", 
      "@type": "Person", 
      "name": "Garc\u0131a-Redondo, Fernando"
    }, 
    {
      "affiliation": "Imperial College London", 
      "@type": "Person", 
      "name": "Georgiou, Pantelis"
    }, 
    {
      "affiliation": "ARM Research", 
      "@type": "Person", 
      "name": "Das, Shidhartha"
    }
  ], 
  "headline": "A Time-Domain Current-Mode MAC Engine for Analogue Neural Networks in Flexible Electronics", 
  "image": "https://zenodo.org/static/img/logos/zenodo-gradient-round.svg", 
  "datePublished": "2019-10-19", 
  "url": "https://zenodo.org/record/3741945", 
  "@type": "ScholarlyArticle", 
  "keywords": [
    "Flexible Electronics", 
    "MAC Operation", 
    "Neural Networks", 
    "Analogue Signal Processing", 
    "Wearable Sensors"
  ], 
  "@context": "https://schema.org/", 
  "identifier": "https://doi.org/10.1109/BIOCAS.2019.8919190", 
  "@id": "https://doi.org/10.1109/BIOCAS.2019.8919190", 
  "workFeatured": {
    "alternateName": "BioCAS", 
    "location": "Nara, Japan", 
    "@type": "Event", 
    "name": "2019 IEEE Biomedical Circuits and Systems Conference"
  }, 
  "name": "A Time-Domain Current-Mode MAC Engine for Analogue Neural Networks in Flexible Electronics"
}