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Quantization Error Analysis

February 2, 2019 by 3200 Creative

Quantization Error Analysis

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  1. Question 1 of 3
    1. Question

    Errors due to rounding signals to the nearest quantization interval are easy to predict and are usually modeled as a sum of two or three sinusoids.

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  2. Question 2 of 3
    2. Question

    Let e_q[n] be the difference or error between the original signal and the quantized signal and \Delta be the smallest interval between quantized values of the signal. Which of the following statements are correct for the model of e_q[n] described in the lecture? Select all that apply.

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  3. Question 3 of 3
    3. Question

    If the number of bits used to quantize a signal is increased from 14 bits to 16 bits and all else remains the same, what happens to the quantization noise power?

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  • Introduction to Sampling and Reconstruction

  • Aliasing and the Sampling Theorem Simplified

  • Fourier Transform Interpretation of Sampling

  • Reconstruction and the Sampling Theorem

  • Reconstruction and the Sampling Theorem Examples

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  • Equivalent Analog Filtering

  • Practical Sampling: Anti-Aliasing Filters

  • Practical Reconstruction: The Zero-Order Hold

  • Practical Digital Filtering and Oversampling

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  • Downsampling: Reducing the Sampling Rate

  • Upsampling: Increasing the Sampling Rate

  • Analog to Digital Conversion: Quantization and Coding

  • Analysis of Quantization Error

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  • Introduction to Signal Estimation and Detection Theory

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