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Discrete Time Signal Processing: Finite Word Length effects in Digital Filters
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Discrete Time Signal Processing: Finite Word Length effects in Digital Filters
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25 Questions

1. An effective remedy for curing the problem of overflow oscillations is to modify the adder characteristic.
2. What is the step size or the resolution of an A/D converter?
3. How many quantization errors are present in one complex valued multiplication?
4. What is the signal-to-noise ratio?
5. How many number of butterflies are required per output point in FFT algorithm?
6. What is the necessary and sufficient condition for a second order filter that no zero-input overflow limit cycles occur?
7. The limit cycle mode with zero input, which occurs as a result of rounding the multiplications, corresponds to an equivalent second order system with poles at z=±1.
8. What is the type of quantizer, if a Zero is assigned a quantization level?
9. What is the type of quantizer, if a Zero is assigned a decision level?
10. How many number of bits are required to compute the DFT of a 1024 point sequence with a SNR of 30db?
11. In recursive systems, which of the following is caused because of the nonlinearities due to the finite-precision arithmetic operations?
12. In the practical A/D converters, if the difference between the values at which the first transition and the last transition occur is not equal to FS '
13. What is the term used to describe the range of an A/D converter for uni-polar signals?
14. What is the model that has been adopt for characterizing round of errors in multiplication?
15. What is the range of values called as to which the amplitudes of the output during a limit cycle ae confined to?
16. What is the term used to describe the range of an A/D converter for bipolar signals?
17. The 4N quantization errors are mutually uncorrelated.
18. If the dynamic range of the signal is smaller than the range of quantizer, the samples that exceed the quantizer are clipped, resulting in large quantization error.
19. Every fourfold increase in the size N of the DFT requires an additional bit in computational precision to offset the additional quantization errors.
20. What is the range in which the quantization errors due to rounding off are uniformly distributed as random variables if Δ=2-b?
21. The quantization inherent in the finite precision arithmetic operations render the system linear.
22. Limit cycles in the recursive are directly attributable to which of the following?
23. How is the variance of the quantization error related to the size of the DFT?
24. The 4N quantization errors are correlated with the sequence {x(n)}.
25. The oscillations in the output of the recursive system are called as '

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