rdf-syntax-grammar
mods:
  schema location: http://www.loc.gov/mods/v3 http://www.loc.gov/standards/mods/v3/mods-3-2.xsd
  title info:
    title: Compact and Fast Machine Learning Accelerator for IoT Devices
  name:
    name part: Huang, Hantao.
    role:
      role term: creator
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: Yu, Hao.
    role:
      role term: author.
    role:
      role term: aut
    role:
      role term: http://id.loc.gov/vocabulary/relators/aut
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: si
    date issued: 2019
    edition: 1st ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: IX, 149 p. 76 illus., 61 illus. in color. online resource.
  abstract: This book presents the latest techniques for machine learning based data analytics on IoT edge devices. A comprehensive literature review on neural network compression and machine learning accelerator is presented from both algorithm level optimization and hardware architecture optimization. Coverage focuses on shallow and deep neural network with real applications on smart buildings. The authors also discuss hardware architecture design with coverage focusing on both CMOS based computing systems and the new emerging Resistive Random-Access Memory (RRAM) based systems. Detailed case studies such as indoor positioning, energy management and intrusion detection are also presented for smart buildings.
  table of contents: Computing on Edge Devices in Internet-of-things (IoT) -- The Rise of Machine Learning in IoT system -- Least-squares-solver for Shadow Neural Network -- Tensor-solver for Deep Neural Network -- Distributed-solver for Networked Neural Network -- Conclusion.
  note: by Hantao Huang, Hao Yu.
  subject:
    topic: Computational intelligence
  subject:
    topic: Microprocessors
  subject:
    topic: Mathematical optimization
  subject:
    topic: Computational Intelligence
  subject:
    topic: Processor Architectures
  subject:
    topic: Optimization
  classification: Q342
  classification: 006.3
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Computer Architecture and Design Methodologies
  identifier: 9789811333231
  identifier: https://doi.org/10.1007/978-981-13-3323-1
  record info:
    record creation date: 181207
    record change date: 20191022093108.0
    record identifier: 978-981-13-3323-1