Stochastic-computing based brainwave LSI towards an intelligence edge

Naoya Onizawa, Warren J. Gross, Takahiro Hanyu

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

Abstract

Stochastic computing has been recently studied for soft-error-resilient hardware and approximate computing, such as image processing and machine learning. This paper presents stochastic-computing based brainware (brain-inspired) hardware and discusses the advantages and disadvantages with the recent developments. In addition, several brainware LSIs (BLSIs) towards an intelligence edge are introduced, such as physiological models and neural networks.

Original languageEnglish
Title of host publication2019 26th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages434-437
Number of pages4
ISBN (Electronic)9781728109961
DOIs
Publication statusPublished - 2019 Nov
Event26th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019 - Genoa, Italy
Duration: 2019 Nov 272019 Nov 29

Publication series

Name2019 26th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019

Conference

Conference26th IEEE International Conference on Electronics, Circuits and Systems, ICECS 2019
CountryItaly
CityGenoa
Period19/11/2719/11/29

Keywords

  • Neural networks
  • Neuromorphic computing
  • Stochastic computing

ASJC Scopus subject areas

  • Electrical and Electronic Engineering
  • Control and Optimization
  • Computer Networks and Communications
  • Hardware and Architecture

Fingerprint Dive into the research topics of 'Stochastic-computing based brainwave LSI towards an intelligence edge'. Together they form a unique fingerprint.

Cite this