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Previous Year Exam Questions for Advanced Digital Signal Processing - ADSP of 2018 - CEC by Bput Toppers

  • Advanced Digital Signal Processing - ADSP
  • 2018
  • PYQ
  • Biju Patnaik University of Technology Rourkela Odisha - BPUT
  • Electrical Engineering
  • B.Tech
  • 3 Offline Downloads
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Part – B (Answer any four questions) Q3 a) Given a signal ( ) ↔ ( ) , such that ( ) = 0 for | | > . The signal is decimated by a factor D=2 to get ( ). Sketch ( ) and ( ) , and justify whether ( ) can be reconstructed from the signal ( ) or not. b) What do you understand by integer-band-positioned discrete time signals? Explain with spectral diagrams, the effect of down-sampling on an even-band-positioned bandpass signal. (10) (5) Q4 a) Explain sub-band coding of speech signal with proper block diagram. b) What do you mean by uniform analysis filer bank? Give the expressions for impulse response, frequency response and system function of such a filter. Draw the frequency response of a 4-component analysis filer bank. (10) (5) Q5 a) Derive the time-domain expression for the output of Forward Linear Prediction Error filter and draw the direct form-1 structure for the filter. Explain what Normal Equations are in reference to this error function expression. b) What is the relationship between Forward Linear Prediction Error Filter system function ( ) and Backward Linear Prediction Error Filter system function ( ) . Determine the reflection coefficients { } of the lattice filter corresponding to the FIR filter described by the system function : 1 H (z)  A 2 (z)  1  2 z 1  z 2 3 (10) Q6 a) Discuss Welch method for power spectrum estimation as an modified form of Bartlett method. b) Prove that periodogram is not a consistent estimate of the true power density spectrum. (10) Q7 a) Differentiate between direct method and indirect method of energy density spectrum estimation. Explain the leakage problem encountered in the computation of energy density spectrum from a finite-duration signal. b) Explain the Bartlett method of power spectrum estimation with supporting mathematical expressions. (10) Q8 a) What do you understand by noise cancellation? Explain adaptive noise cancellation with block diagram and supporting mathematical expressions. b) Define mean square error for an adaptive linear combiner. Hence derive the Wiener- Hopf equation for optimum filter coefficients for the same. (10) Q9 a) Derive the relationship between the autocorrelation function ( ) and the filter parameters, if the power spectral density of the stationary random process ( ) is a rational function, and the filter generates the random process by filtering the white noise sequence ( ). b) Explain rational power spectra for a stationary random process. Also explain the three specific cases of rational power spectra? Write the difference equation for each of them. (10) (5) (5) (5) (5) (5)

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