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Introduction to Estimation Theory

February 2, 2019 by 3200 Creative

Introduction to Estimation Theory

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  1. Question 1 of 4
    1. Question

    Which of the following are true about parameter estimation? Select all that apply.

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  2. Question 2 of 4
    2. Question

    An unbiased estimator has which of the following properties

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  3. Question 3 of 4
    3. Question

    The variance of an estimator is the average of the squared difference between the estimated and true values.

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  4. Question 4 of 4
    4. Question

    The mean-squared error of an estimator is the sum of the variance and the square of the bias.

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Course Lessons

  • Introduction to Estimation Theory

  • Parameter Estimation Criteria

  • Maximum Likelihood Estimation Examples

  • Introduction to Detection Theory

  • The Likelihood Ratio Test

  • The Generalized Likelihood Ratio Test

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

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