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This section includes 20 Mcqs, each offering curated multiple-choice questions to sharpen your Digital Signal Processing knowledge and support exam preparation. Choose a topic below to get started.
1. |
How many number of bits are required to compute the DFT of a 1024 point sequence with a SNR of 30db? |
A. | 15 |
B. | 10 |
C. | 5 |
D. | 20 |
Answer» B. 10 | |
2. |
What is the signal-to-noise ratio? |
A. | σX2.σq2 |
B. | σX2/σq2 |
C. | σX2+σq2 |
D. | σX2-σq2 |
Answer» C. σX2+σq2 | |
3. |
What is the variance of the output DFT coefficients |X(k)|? |
A. | \(\frac{1}{N}\) |
B. | \(\frac{1}{2N}\) |
C. | \(\frac{1}{3N}\) |
D. | \(\frac{1}{4N}\) |
Answer» D. \(\frac{1}{4N}\) | |
4. |
Every fourfold increase in the size N of the DFT requires an additional bit in computational precision to offset the additional quantization errors. |
A. | True |
B. | False |
Answer» B. False | |
5. |
What is the range in which the quantization errors due to rounding off are uniformly distributed as random variables if Δ=2-b? |
A. | (0,Δ) |
B. | (-Δ,0) |
C. | (-Δ/2,Δ/2) |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
6. |
EVERY_FOURFOLD_INCREASE_IN_THE_SIZE_N_OF_THE_DFT_REQUIRES_AN_ADDITIONAL_BIT_IN_COMPUTATIONAL_PRECISION_TO_OFFSET_THE_ADDITIONAL_QUANTIZATION_ERRORS.?$ |
A. | True |
B. | False |
Answer» B. False | |
7. |
What is the signal-to-noise ratio?$ |
A. | σ<sub>X</sub><sup>2</sup>. σ<sub>q</sub><sup>2</sup> |
B. | σ<sub>X</sub><sup>2</sup>/ σ<sub>q</sub><sup>2</sup> |
C. | σ<sub>X</sub><sup>2</sup>+ σ<sub>q</sub><sup>2</sup> |
D. | σ<sub>X</sub><sup>2</sup>-σ<sub>q</sub><sup>2</sup> |
Answer» C. ‚âà√¨‚àö√¢<sub>X</sub><sup>2</sup>+ ‚âà√¨‚àö√¢<sub>q</sub><sup>2</sup> | |
8. |
What_is_the_variance_of_the_output_DFT_coefficients_|X(k)|?$ |
A. | 1/N |
B. | 1/2N |
C. | 1/3N |
D. | 1/4N |
Answer» D. 1/4N | |
9. |
How many number of bits are required to compute the FFT of a 1024 point sequence with a SNR of 30db? |
A. | 11 |
B. | 10 |
C. | 5 |
D. | 20 |
Answer» B. 10 | |
10. |
What is the value of the variance of quantization error in FFT algorithm, compared to that of direct computation? |
A. | Greater |
B. | Less |
C. | Equal |
D. | Cannot be compared |
Answer» D. Cannot be compared | |
11. |
How many number of butterflies are required per output point in FFT algorithm? |
A. | N |
B. | N+1 |
C. | 2N |
D. | N-1 |
Answer» E. | |
12. |
How_many_number_of_bits_are_required_to_compute_the_DFT_of_a_1024_point_sequence_with_a_SNR_of_30db? |
A. | 15 |
B. | 10 |
C. | 5 |
D. | 20 |
Answer» B. 10 | |
13. |
How is the variance of the quantization error related to the size of the DFT? |
A. | Equal |
B. | Inversely proportional |
C. | Square proportional |
D. | Proportional |
Answer» E. | |
14. |
The 4N quantization errors are correlated with the sequence {x(n)}. |
A. | True |
B. | False |
Answer» C. | |
15. |
The 4N quantization errors are mutually uncorrelated. |
A. | True |
B. | False |
Answer» B. False | |
16. |
What is the range in which the quantization errors due to rounding off are uniformly distributed as random variables if Δ=2-b?$ |
A. | (0,Δ) |
B. | (-Δ,0) |
C. | (-Δ/2,Δ/2) |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
17. |
What is the total number of quantization errors in the computation of single point DFT of a sequence of length N? |
A. | 2N |
B. | 4N |
C. | 8N |
D. | 12N |
Answer» C. 8N | |
18. |
How many quantization errors are present in one complex valued multiplication? |
A. | One |
B. | Two |
C. | Three |
D. | Four |
Answer» E. | |
19. |
What is the model that has been adopt for characterizing round of errors in multiplication? |
A. | Multiplicative white noise model |
B. | Subtractive white noise model |
C. | Additive white noise model |
D. | None of the mentioned |
Answer» D. None of the mentioned | |
20. |
The effect of round off errors due to the multiplications performed in the DFT with fixed point arithmetic is known as Quantization error. |
A. | True |
B. | False |
Answer» B. False | |