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: Emerging capabilities and applications of artificial higher order neural networks
  name:
    name part: Zhang, Ming
    name part: 1949 July 29-
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: IGI Global Online
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: pau
    date issued: 2021
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource.
  table of contents: Section 1. Models of artificial higher order neural networks. Chapter 1. Models of artificial higher order neural networks ; Chapter 2. Models of artificial multi-polynomial higher order neural networks ; Chapter 3. Group models of artificial polynomial and trigonometric higher order neural networks -- Section 2. Artificial higher order neural networks for economics and business. Chapter 4. SAS nonlinear models or artificial higher order neural network nonlinear models? ; Chapter 5. Time series data analysis by ultra-high frequency trigonometric higher order neural networks ; Chapter 6. Financial data prediction by artificial sine and cosine trigonometric higher order neural networks -- Section 3. Artificial higher order neural networks for modeling and simulation. Chapter 7. Data classification using ultra-high frequency SINC and trigonometric higher order neural networks ; Chapter 8. Data simulations using cosine and sigmoid higher order neural networks ; Chapter 9. Rainfall estimation using neuron-adaptive higher order neural networks -- Section 4. Artificial higher order neural networks for control and recognition. Chapter 10. Control signal generator based on ultra-high frequency polynomial and trigonometric higher order neural networks ; Chapter 11. Data pattern recognition based on ultra-high frequency sigmoid and trigonometric higher order neural networks ; Chapter 12. Face recognition based on higher order neural network group-based adaptive tolerance Trees.
  note: Ming Zhang.
  note: "Premier Reference Source" -- taken from front cover.
  note: Electronic resource.
  note: Includes bibliographical references and index.
  subject:
    topic: Neural networks (Computer science)
    topic: Industrial applications
  subject:
    topic: Engineering
    topic: Data processing
  subject:
    topic: Business
    topic: Decision making
    topic: Data processing
  classification: QA76.87 .Z4745 2021
  classification: 006.3/2
  related item:
    title info:
      title: Emerging capabilities and applications of artificial higher order neural networks
    name:
      name part: Zhang, Ming, 1949 July 29-
    origin info:
      publisher: Hershey, PA : Engineering Science Reference, an imprint of IGI Global, [2020]
    identifier: (DLC) 2019054311
  related item:
    title info:
      title: Advances in computational intelligence and robotics (ACIR) book series
  identifier: 9781799835660
  identifier: 1799835669
  identifier: 1799835650
  identifier: 9781799835653
  identifier: 9781799835639
  identifier: 9781799835646
  identifier: 2019054312
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: NhCcYBP
    record creation date: 191213
    record change date: 20211018101437.0
    record identifier: in00004438330