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:
    non sort: A
    title: First Course in Statistics for Signal Analysis
  name:
    name part: Woyczyński, Wojbor A.
    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: 3rd ed. 2019.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: electronic
    form: electronic resource
    reformatting quality: access
    form: remote
    extent: XVIII, 332 p. 95 illus., 69 illus. in color. online resource.
  abstract: This essentially self-contained, deliberately compact, and user-friendly textbook is designed for a first, one-semester course in statistical signal analysis for a broad audience of students in engineering and the physical sciences. The emphasis throughout is on fundamental concepts and relationships in the statistical theory of stationary random signals, explained in a concise, yet fairly rigorous presentation. Topics and Features: · Fourier series and transforms-fundamentally important in random signal analysis and processing-are developed from scratch, emphasizing the time-domain vs. frequency-domain duality; · Basic concepts of probability theory, laws of large numbers, the central limit theorem, and statistical parametric inference procedures are presented so that no prior knowledge of probability and statistics is required; the only prerequisite is a basic two-three semester calculus sequence; · Computer simulation algorithms of stationary random signals with a given power spectrum density; · Complementary bibliography for readers who wish to pursue the study of random signals in greater depth; · Many diverse examples and end-of-chapter problems and exercises. Developed by the author over the course of many years of classroom use, A First Course in Statistics for Signal Analysis, Second Edition may be used by junior/senior undergraduates or graduate students in electrical, systems, computer, and biomedical engineering, as well as the physical sciences. The work is also an excellent resource of educational and training material for scientists and engineers working in research laboratories. This third edition contains two additional chapters that present wavelets and the uncertainty principle, and the forecasting problems for stationary time series. These two topics are essential for students to attain a deeper understanding of statistical analysis of random signals. Reviews from previous editions: A First Course in Statistics for Signal Analysis is a small, den…
  table of contents: Description of Signals -- Spectral Representation of Deterministic Signals: Fourier Series and Transforms -- Uncertainty Principle and Wavelet Transforms -- Random Variables and Random Vectors -- Stationary Signals -- Power Spectra of Random Signals -- Transmission of Stationary Signals through Linear Systems -- Optimization of Signal-to-Noise Ratio in Linear Systems -- Gaussian Signals, Covariance Matrices, and Sample Path Properties -- Spectral Representation of Discrete-Time Signals and Their Computer Simulations -- Prediction Theory for Stationary Random Signals -- Solutions to Selected Problems and Exercises.
  note: by Wojbor A. Woyczyński.
  subject:
    topic: Statistics
  subject:
    topic: Fourier analysis
  subject:
    topic: Signal processing
  subject:
    topic: Image processing
  subject:
    topic: Speech processing systems
  subject:
    topic: Statistics for Engineering, Physics, Computer Science, Chemistry and Earth Sciences
  subject:
    topic: Fourier Analysis
  subject:
    topic: Signal, Image and Speech Processing
  classification: QA276-280
  classification: 519.5
  related item:
    title info:
      title: Springer eBooks
  related item:
    title info:
      title: Statistics for Industry, Technology, and Engineering
  identifier: 9783030209087
  identifier: https://doi.org/10.1007/978-3-030-20908-7
  record info:
    record creation date: 191004
    record change date: 20191024121244.0
    record identifier: 978-3-030-20908-7