• Skip to primary navigation
  • Skip to main content
  • Skip to primary sidebar

ALLSIGNALPROCESSING.COM

Learn signal processing online

  • Home
  • Courses
  • Courses
  • About
  • FAQ
  • My Account
  • Blog
  • News
  • Contact
  • Login
  • Logout
  • Get All Access

Random Signal Characterization

March 1, 2019 by 3200 Creative

The ability to deal with uncertainty in the characteristics of signals is a very important part of advanced signal processing methods. This series of seven lessons introduces you to tools from probability for describing signals that are modeled as having random characteristics. You will learn about auto- and cross-correlation for describing random signals in the time domain, and power spectra, cross spectra, and coherence for describing random signals in the frequency domain. You will also learn how to represent random signals as the output of a linear time-invariant system with white noise input using autoregressive, moving average, and autoregressive moving average models.

Course Content

Lessons Status
1

Introduction to Random Signal Representations

2

Multivariable Random Signal Characterization

3

Random Processes and Stationarity

4

The Power Spectral Density

5

Cross Spectra and Coherence

6

LTI System Models for Random Signals

7

Autoregressive Models: The Yule-Walker Equations

Filed Under: Uncategorized

Primary Sidebar

Course Lessons

  • Introduction to Random Signal Representations

  • Multivariable Random Signal Characterization

  • Random Processes and Stationarity

  • The Power Spectral Density

  • Cross Spectra and Coherence

  • LTI System Models for Random Signals

  • Autoregressive Models: The Yule-Walker Equations

Courses

  • Foundations

  • Time Domain LTI Systems

  • Fourier Series and Transforms

  • Sampling and Reconstruction

  • The DFT and Applications

  • The Z-Transform

  • Intro to Filter Design

  • IIR Filter Design

  • FIR Filter Design

  • Random Signal Characterization

  • Basis Representations of Signals

  • Estimation of Power Spectra and Coherence

  • Introduction to Signal Estimation and Detection Theory

  • MMSE Filtering and Least-Squares Problems

Copyright © 2023 ALLSIGNALPROCESSING.COM | Site Design by 3200 Creative

  • Terms of Service
  • Privacy Policy
  • Contact