Data compression unit 4 mcq
1. Which of the following characterizes a quantizer
(A) Quantization results in a non-reversible loss of information
(B) A quantizer always produces uncorrelated output samples
(C) The output of a quantizer has the same entropy rate as the input
(D) None of the above
2. What is the signal-to-noise ratio (SNR)?
(A) The ratio of the average squared value of the source output and the squared error of the source output
(B) The ratio of the average squared value of the source output and the mean squared error of the source output
(C) The ratio of the average squared value of the source output and the absolute difference measure of the source output
(D) None of the above
3. The output signal of a scalar quantizer has property
(A) The output is a discrete signal with a finite symbol alphabet
(B) The output is a discrete signal with a countable symbol alphabet (but not necessarily a finite symbol alphabet)
(C) The output signal may be discrete or continuous
(D) None of the above
4. What is a Lloyd quantizer?
(A) For a given source, the Lloyd quantizer is the best possible scalar
quantizer in ratedistortion sense. That means, there does not exist any
other scalar quantizer that yields a smaller distortion at the same
rate.
(B) The output of a Lloyd quantizer is a discrete signal with a uniform pmf
(C) Both (A) and (B)
(D) A Lloyd quantizer is the scalar quantizer that yields the minimum
distortion for a given source and a given number of quantization
intervals.
5. Which of the following statement is correct for comparing scalar quantization and vector quantization?
(A) Vector quantization improves the performance only for sources with
memory. For iid sources, the best scalar quantizer has the same
efficiency as the best vector quantizer
(B) Vector quantization does not improve the rate-distortion performance
relative to scalar quantization, but it has a lower complexity
(C) By vector quantization we can always improve the rate-distortion performance relative to the best scalar quantizer
(D) All of the above
6. If {x}n is the source output and {y}n is the reconstructed sequence, then the squared error measure is given by
(A) d(x, y) = (y - x)2
(B) d(x, y) = (x - y)2
(C) d(x, y) = (y + x)2
(D) d(x, y) = (x - y)4
7. If {x}n is the source output and {y}n is the reconstructed sequence, then the absolute difference measure is given by
(A) d(x, y) = |y - x|
(B) d(x, y) = |x - y|
(C) d(x, y) = |y + x|
(D) d(x, y) = |x - y|2
8. The process of representing a _______ possibly infinite set of values with a much _______ set is called quantization
(A) Large, smaller
(B) Smaller, large
(C) None of these
9. The set of inputs and outputs of a quantizer can be
(A) Only scalars
(B) Only vectors
(C) Scalars or vectors
(D) None of these
10. Which of the folowing is/are correct for uniform quantizer
(A) The simplest type of quantizer is the uniform quantizer
(B) All intervals are the same size in the uniform quantizer, except possibly for the two outer intervals
(C) The decision boundaries are spaced evenly
(D) All of the above
11. If a Zero is assigned a decision level, then what is the type of quantizer?
(A) A midtread quantizer
(B) A midrise quantizer
(C) A midtreat quantizer
(D) None of the above
12. If a Zero is assigned a quantization level, then what is the type of quantizer?
(A) A midtread quantizer
(B) A midrise quantizer
(C) A midtreat quantizer
(D) None of the above
13. The main approaches to adapting the quantizer parameters:
(A) An off-line or forward adaptive approach
(B) An on-line or backward adaptive approach
(C) Both
(D) None of the above
14. Uniform quantizer is also called as
(A) Low rise quantizer
(B) High rise quantizer
(C) Mid rise quantizer
(D) None of the above
15. Non uniform quantizer ______ distortion.
(A) Decrease
(B) Increase
(C) Doesn't change
(D) None of the above
16. The spectral density of white noise is ______.
(A) Poisson
(B) Exponential
(C) Uniform
(D) Gaussian
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