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: Bayesian estimation and tracking
    sub title: a practical guide
  name:
    name part: Haug, Anton J.
    name part: 1941-
    role:
      role term: creator
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: nju
    date issued: 2012
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (xxvi, 369 pages) : illustrations
  abstract: A practical approach to estimating and tracking dynamic systems in real-worl applications Much of the literature on performing estimation for non-Gaussian systems is short on practical methodology, while Gaussian methods often lack a cohesive derivation. Bayesian Estimation and Tracking addresses the gap in the field on both accounts, providing readers with a comprehensive overview of methods for estimating both linear and nonlinear dynamic systems driven by Gaussian and non-Gaussian noices. Featuring a unified approach to Bayesian estimation and tracking, the book emphasizes the derivation of all tracking algorithms within a Bayesian framework and describes effective numerical methods for evaluating density-weighted integrals, including linear and nonlinear Kalman filters for Gaussian-weighted integrals and particle filters for non-Gaussian cases. The author first emphasizes detailed derivations from first principles of eeach estimation method and goes on to use illustrative and detailed step-by-step instructions for each method that makes coding of the tracking filter simple and easy to understand.
  note: Anton J. Haug.
  note: Electronic resource.
  note: Includes bibliographical references and index.
  subject:
    topic: Automatic tracking
    topic: Mathematics
  subject:
    topic: Bayesian statistical decision theory
  subject:
    topic: Estimation theory
  subject:
    topic: Automatic tracking
    topic: Mathematics
  subject:
    topic: Bayesian statistical decision theory
  subject:
    topic: Estimation theory
  subject:
    topic: Mathematics
  subject:
    topic: MATHEMATICS / Probability & Statistics / Bayesian Analysis
  classification: QA279.5 .H38 2012
  classification: 519.5/42 519.542
  related item:
    title info:
      title: Bayesian Estimation and Tracking : A Practical Guide
    name:
      name part: Haug, Anton J.
    origin info:
      publisher: Hoboken : John Wiley & Sons, c2012
  related item:
    title info:
      title: Wiley Online Library
  identifier: 1118287797 (electronic bk.)
  identifier: 1118287835 (electronic bk.)
  identifier: 9781118287798 (electronic bk.)
  identifier: 9781118287835 (electronic bk.)
  identifier: 10.1002/9781118287798 Wiley InterScience
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: EBLCP
    record creation date: 120604
    record change date: 20210728124919.0
    record identifier: in00002770374
    language of cataloging:
      language term: eng