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: Linear Algebra, Signal Processing, and Wavelets - A Unified Approach
    sub title: Python Version
  name:
    name part: Ryan, Øyvind.
    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: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    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: XXVII, 364 p. 103 illus., 29 illus. in color. online resource.
  abstract: This book offers a user friendly, hands-on, and systematic introduction to applied and computational harmonic analysis: to Fourier analysis, signal processing and wavelets; and to their interplay and applications. The approach is novel, and the book can be used in undergraduate courses, for example, following a first course in linear algebra, but is also suitable for use in graduate level courses. The book will benefit anyone with a basic background in linear algebra. It defines fundamental concepts in signal processing and wavelet theory, assuming only a familiarity with elementary linear algebra. No background in signal processing is needed. Additionally, the book demonstrates in detail why linear algebra is often the best way to go. Those with only a signal processing background are also introduced to the world of linear algebra, although a full course is recommended. The book comes in two versions: one based on MATLAB, and one on Python, demonstrating the feasibility and applications of both approaches. Most of the code is available interactively. The applications mainly involve sound and images. The book also includes a rich set of exercises, many of which are of a computational nature.
  table of contents: 1. Sound and Fourier series -- 2. Digital Sound and Discrete Fourier Analysis -- 3. Discrete Time Filters -- 4. Motivation for Wavelets and Some Simple Examples -- 5. The Filter Representation of Wavelets -- 6. Constructing Interesting Wavelets -- 7. The Polyphase Representation of Filter Bank Transforms -- 8. Digital Images -- 9. Using Tensor Products to Apply Wavelets to Images -- A Basic Linear Algebra.
  note: by Øyvind Ryan.
  subject:
    topic: Algebras, Linear
  subject:
    topic: Computer mathematics
  subject:
    topic: Applied mathematics
  subject:
    topic: Engineering mathematics
  subject:
    topic: Signal processing
  subject:
    topic: Image processing
  subject:
    topic: Speech processing systems
  subject:
    topic: Fourier analysis
  subject:
    topic: Linear Algebra
  subject:
    topic: Computational Science and Engineering
  subject:
    topic: Mathematical and Computational Engineering
  subject:
    topic: Signal, Image and Speech Processing
  subject:
    topic: Fourier Analysis
  classification: QA184-205
  classification: 512.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Springer Undergraduate Texts in Mathematics and Technology
  identifier: 9783030029401
  identifier: https://doi.org/10.1007/978-3-030-02940-1
  record info:
    record creation date: 190226
    record change date: 20191021231858.0
    record identifier: 978-3-030-02940-1