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Unit 2
The document contains 35 multiple choice questions about topics related to digital communication systems including power spectral density, energy spectral density, autocorrelation, random variables, random processes, source coding methods, quantization, and stochastic processes. Specifically, it tests knowledge about the properties of power spectral density functions, Wiener-Khinchin theorem, Parseval's theorem, autocorrelation functions, random variables and their distributions, characteristics of random processes like stationarity, source coding techniques like PCM, DPCM, and delta modulation, quantization noise, and properties of distributions like binomial and Poisson.
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Unit 2
- 1. NEC 602 DigitalCommunication MCQ for unit 2 1. Power spectral density function is a ? a) Real and even function b) Non negative function c) Periodic d) All of the mentioned 2. Energy spectral density defines a) Signal energy per unit area b) Signal energy per unit bandwidth c) Signal power per unit area d) Signal power per unit bandwidth 3. Power spectrum describes distribution of _________ under frequency domain. a) Mean b) Variance c) Gaussian d) None of the mentioned 4. How can power spectral density of non periodic signal be calculated? a) By integrating b) By truncating c) By converting to periodic d) None of the mentioned 5. What is Wiener-Khinchin theorem? a) Spectral density and auto-covariance makes a fourier transform pair b) Spectral density and auto-correlatioon makes a fourier tranform pair c) Spectral density and variance makes a fourier tranform pair d) None of the mentioned 6. According to Parseval’s theorem the energy spectral density curve is equal to? a) Area under magnitude of the signal b) Area under square of the magnitude of the signal c) Area under square root of magnitude of the signal d) None of the mentioned
- 2. 7. Spectogram isthe graph plotted against? a) Frequency domain b) Time domain c) Both of the mentioned d) None of the mentioned 8. Autocorrelation is a function which matches – a) Two same signals b) Two different signal c) One signal with its delayed version d) None of the mentioned 9. Autocorrelation is a function of a) Time b) Frequency c) Time difference d) Frequency difference 10. Autocorrelation is maximum at _______ a) Unity b) Origin c) Infinite point d) None of the mentioned 11. Autocorrelation function of periodic signal is equal to _______ a) Energy of the signal b) Power of the signal c) Its area in frequency domain d) None of the mentioned 12. Autocorrelation is a _______ function. a) Real and even b) Real and odd c) Complex and even d) Complex and odd 13. Autocorrelation function of white noise will have ? a) Strong peak b) Infinite peak c) Weak peak d) None of the mentioned 14. Random variables give relationship between _____ a) Two random events b) Probability of occurence of two random events c) Random event and a real number d) Random event and its probability of occurence
- 3. 15. The distributionfunction of random variable is a) P(X less than or equal to x) b) P(X greater than or equal to x) c) P(X less than x) d) P(X greater than x) 16. The distribution function of -(infinity) and (infinity) is _____ a) 0 and 1 b) 1 and 0 c) Both 0 d) Both 1 17. The value of probability density function of random variable is a) Positive function b) Negative function c) Zero d) One 18. Which gives the measure of randomness of the random variable ? a) Mean b) Variance c) Standard variance d) Pdf 19. Random process is a function of ______ a) Random event and time b) Random event and frequency c) Random event and real number d) None of the mentioned 20. A random process is called as stationary in strict sense if a) Its statistics vary with shift in time origin b) Its statistics does not vary with shift in time origin c) Its autocorrelation vary with shift in time d) Its autocorrelation does not vary with shift in time 21. For stationary process, autocorrelation function depends on a) Time b) Time difference c) Does not depend on time d) None of the mentioned 22. Autocorrelation function is maximum at a) Origin b) Infinity c) Both of the mentioned d) None of the mentioned
- 4. 23. Standard deviationis ______ a) Rms value of dc b) Rms value or ac c) Either ac or dc d) Neither dc nor ac 24. The average power of white noise is a) Zero b) Unity c) Infinity d) Between zero and one 25. White noise has _____ mean and ______ variance. a) Zero and zero b) Finite and zero c) Zero and finite d) One and zero 26. Which method is much better and efficient? a) Vector quantization b) Scalar quantization c) Both of the mentioned d) None of the mentioned 27. Analog source coding method are a) Temporal waveform coding b) Spectral waveform coding c) Model based coding d) All of the mentioned 28. The source output in PCM and DPCM is quasi stationary. a) True b) False 29. Which reduces the dynamic range of quantization noise in PCM ? a) Non uniform quantizer b) Uniform quantizer c) Adaptive quantizer d) None of the mentioned 30. The type of distortion which occurs in delta modulation are a) Slope overload distortion b) Granular noise c) Both of the mentioned d) None of the mentioned 31. Binomial distribution deals with a) Continuous random variable b) Discrete random variable
- 5. c) Both ofthe mentioned d) None of the mentioned 32. In poisson distribution mean is ______ variance. a) Greater than b) Lesser than c) Equal to d) Does not depend on 33. Stochastic process are a) Random in nature b) Are function of time c) Both of the mentioned d) None of the mentioned 34. Stochastic processes are a) Strict sense stationary process b) Wide sense stationary process 35. Gaussian process is a a) Wide sense stationary process b) Strict sense stationary process c) Both of the mentioned d) None of the mentioned