Performance and Cost Evaluations of Online Sequential Learning and Unsupervised Anomaly Detection Core

Tomoya Itsubo, Mineto Tsukada, Hiroki Matsutani

研究成果: Conference contribution

抄録

Toward on-device learning on IoT devices, this paper implements an online sequential learning and unsupervised anomaly detection core and explores its design options, such as pipeline structure. They are evaluated in terms of performance and cost.

本文言語English
ホスト出版物のタイトルIEEE Symposium on Low-Power and High-Speed Chips and Systems, COOL CHIPS 2019 - Proceedings
出版社Institute of Electrical and Electronics Engineers Inc.
ISBN(電子版)9781728117485
DOI
出版ステータスPublished - 2019 5 23
イベント22nd IEEE Symposium on Low-Power and High-Speed Chips and Systems, COOL CHIPS 2019 - Yokohama, Japan
継続期間: 2019 4 172019 4 19

出版物シリーズ

名前IEEE Symposium on Low-Power and High-Speed Chips and Systems, COOL CHIPS 2019 - Proceedings

Conference

Conference22nd IEEE Symposium on Low-Power and High-Speed Chips and Systems, COOL CHIPS 2019
CountryJapan
CityYokohama
Period19/4/1719/4/19

ASJC Scopus subject areas

  • Hardware and Architecture
  • Electrical and Electronic Engineering

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