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: Understanding digital signal processing with MATLAB® and solutions
  title info:
    title: MATHnetBASE
  name:
    name part: Poularikas, Alexander D.
    name part: 1933-
    role:
      role term: creator
    role:
      role term: author.
  name:
    name part: Taylor & Francis
  name:
    name part: Taylor and Francis
  type of resource: text
  genre: bibliography
  genre: Electronic books.
  origin info:
    place:
      place term: flu
    date issued: 2017
    edition: First edition.
    issuance: monographic
  language:
    language term: eng
  physical description:
    form: remote
    extent: 1 online resource (471 pages) : 236 illustrations
  abstract: The book discusses receiving signals that most electrical engineers detect and study. The vast majority of signals could never be detected due to random additive signals, known as noise, that distorts them or completely overshadows them. Such examples include an audio signal of the pilot communicating with the ground over the engine noise or a bioengineer listening for a fetus' heartbeat over the mother's. The text presents the methods for extracting the desired signals from the noise. Each new development includes examples and exercises that use MATLAB to provide the answer in graphic forms for the reader's comprehension and understanding.
  table of contents: chapter 1 Continuous and Discrete Signals -- chapter 2 Fourier Analysis of Continuous and Discrete Signals -- chapter 3 The z-Transform, Difference Equations, and Discrete Systems -- chapter 4 Finite Impulse Response (FIR) Digital Filter Design -- chapter 5 Random Variables, Sequences, and Probability Functions -- chapter 6 Linear Systems with Random Inputs, Filtering, and Power Spectral Density -- chapter 7 Least Squares-Optimum Filtering -- chapter 8 Nonparametric (Classical) Spectra Estimation -- chapter 9 Parametric and Other Methods for Spectral Estimation -- chapter 10 Newton's and Steepest Descent Methods -- chapter 11 The Least Mean Square (LMS) Algorithm -- chapter 12 Variants of Least Mean Square Algorithm -- chapter 13 Nonlinear Filtering.
  note: by Alexander D. Poularikas.
  subject:
    topic: TECHNOLOGY & ENGINEERING / Electrical
  subject:
    topic: MATLAB
  subject:
    topic: Matrices And Mathematical Formulas
  subject:
    topic: Probability
  subject:
    topic: Sinusoidal Signals In Noise
  subject:
    topic: Digital Signal Processing
  subject:
    topic: ElectricalEngineeringnetBASE
  subject:
    topic: Mathematics & Statistics for Engineers
  subject:
    topic: Signal processing
    topic: Digital techniques
  classification: TK5102.9 P685 2017
  classification: 621.3822028553
  related item:
    identifier: (DLC) 2017022733
  identifier: 9781315112855
  identifier: http://proxy.library.tamu.edu/login
  record info:
    record content source: FlBoTFG
    record creation date: 180727
    record change date: 20220613175924.0
    record identifier: in00004581533