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Random Processes and Stationarity

February 2, 2019 by 3200 Creative

Random Processes and Stationarity

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  1. Question 1 of 4
    1. Question

    A collection of random variables measured at different indices in time is called a random process.

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  2. Question 2 of 4
    2. Question

    If the statistics describing relationships between elements of a random process are independent of the time one considers in the random process, the process is called

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  3. Question 3 of 4
    3. Question

    The autocovariance for a wide-sense stationary random process depends only on

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  4. Question 4 of 4
    4. Question

    If a random process is ergodic, then we can estimate expectations such as the mean and covariance by

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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

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  • 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

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