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: Information Theory for Electrical Engineers
  name:
    name part: Gazi, Orhan.
    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: si
    date issued: 2018
    edition: 1st ed. 2018.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: IX, 276 p. 122 illus., 2 illus. in color. online resource.
  abstract: This book explains the fundamental concepts of information theory, so as to help students better understand modern communication technologies. It was especially written for electrical and communication engineers working on communication subjects. The book especially focuses on the understandability of the topics, and accordingly uses simple and detailed mathematics, together with a wealth of solved examples. The book consists of four chapters, the first of which explains the entropy and mutual information concept for discrete random variables. Chapter 2 introduces the concepts of entropy and mutual information for continuous random variables, along with the channel capacity. In turn, Chapter 3 is devoted to the typical sequences and data compression. One of Shannon's most important discoveries is the channel coding theorem, and it is critical for electrical and communication engineers to fully comprehend the theorem. As such, Chapter 4 solely focuses on it. To gain the most from the book, readers should have a fundamental grasp of probability and random variables; otherwise, they will find it nearly impossible to understand the topics discussed.
  table of contents: Concept of Information, Discrete Entropy and Mutual Information -- Entropy for Continuous Random Variables Discrete Channel Capacity, Continuous Channel Capacity -- Typical Sequences and Data Compression -- Channel Coding Theorem.
  note: by Orhan Gazi.
  subject:
    topic: Electrical engineering
  subject:
    topic: Coding theory
  subject:
    topic: Information theory
  subject:
    topic: Communications Engineering, Networks
  subject:
    topic: Coding and Information Theory
  classification: TK1-9971
  classification: 621.382
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Signals and Communication Technology
  identifier: 9789811084324
  identifier: https://doi.org/10.1007/978-981-10-8432-4
  record info:
    record creation date: 180309
    record change date: 20191025191930.0
    record identifier: 978-981-10-8432-4