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: Detection of Random Signals in Dependent Gaussian Noise
  name:
    name part: Gualtierotti, Antonio F.
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: SpringerLink (Online service)
  type of resource: text
  origin info:
    place:
      place term: gw
    date issued: 2015
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XXXIV, 1176 p. 5 illus. online resource.
  abstract: The book presents the necessary mathematical basis to obtain and rigorously use likelihoods for detection problems with Gaussian noise. To facilitate comprehension the text is divided into three broad areas – reproducing kernel Hilbert spaces, Cramér-Hida representations and stochastic calculus – for which a somewhat different approach was used than in their usual stand-alone context. One main applicable result of the book involves arriving at a general solution to the canonical detection problem for active sonar in a reverberation-limited environment. Nonetheless, the general problems dealt with in the text also provide a useful framework for discussing other current research areas, such as wavelet decompositions, neural networks, and higher order spectral analysis. The structure of the book, with the exposition presenting as many details as necessary, was chosen to serve both those readers who are chiefly interested in the results and those who want to learn the material from scratch. Hence, the text will be useful for graduate students and researchers alike in the fields of engineering, mathematics and statistics.
  table of contents: Prolog -- Part I: Reproducing Kernel Hilbert Spaces -- Part II: Cramér-Hida Representations -- Part III: Likelihoods -- Credits and Comments -- Notation and Terminology -- References -- Index.
  note: by Antonio F. Gualtierotti.
  subject:
    topic: Mathematics
  subject:
    topic: Functional analysis
  subject:
    topic: Information theory
  subject:
    topic: Probabilities
  subject:
    topic: Mathematics
  subject:
    topic: Probability Theory and Stochastic Processes
  subject:
    topic: Functional Analysis
  subject:
    topic: Information and Communication, Circuits
  classification: QA273.A1-274.9
  classification: QA274-274.9
  classification: 519.2
  related item:
    title info:
      title: Springer eBooks
  identifier: 9783319223155
  identifier: http://dx.doi.org/10.1007/978-3-319-22315-5
  record info:
    record creation date: 151215
    record change date: 20160126020441.0
    record identifier: 978-3-319-22315-5