SAMPLE PAPER OF DIGITAL SIGNAL PROCESSING FOR ELECTRONICS AND COMMUNICATION
TIME: 3 HRS.
NOTE: All the questions from the section-a is compulsory and any 5 from the section-b.
short questions: (each 2 marks)
1. What is Digital Signal Processing.
ans: DSP deals with the manipulation of an information signal to modify or improve it in some way.
2. What do you mean by sampling.
ans: This is the conversion of a continuous- time signal into a discrete – time signal obtained by taking samples of the continuous time signal at discrete time instant.
3. Explain the term quantization.
ans: This is the conversion of a discrete time continuous valued signal into a discrete – time, discrete valued. The value of each signal sample is represented by a value selected from a finite set of possible values. The difference between the unquantized value and quantised one is known as quantization.
4. What are continuous signals?
ans: The signals that varies continuously with time ie, the signal is defined for each value of time is called as continuous time signal.
5. What is Nyquist rate.
ans: FN= 2Fmax
6. List few advantages of dsp.
ans: · easy to store and use, that is why computers use it.
· Digital data is designed and artificially created, so it is efficient.
· Less expensive.
. DSP is easier to reconfigure as it is made up of h/w as well as s/w.
7. What are the classification of discrete-time signals.
ans: energy and power, periodic and aperiodic, symetric and asymetric, causal and non-casual
8. Name 2 properties of z- transform
ans: scaling property, linearity property
9. What do you mean by time variant ?
ans: The signals which do not change with respect to time is known as time invariant.
10. What do you mean by linear ?
ans: The system is said to be linear when it satisfies all the superposition filter.
LONG QUESTIONS: (EACH 10 MARKS)
1. List all the properties of z- transform
ans: Linearity property
Time shifting property
Initial value theorem
Final value theorem
2. What are the differences between the fourier transforms of a discrete time signal with the fourier transform
of a continuous time signals.
ans: Fourier Series is used for periodic signals. It represents the signal by the discrete-time sequence of basis functions with finite and concrete amplitude and phase shift. The basis functions, according to the theory, are harmonics with the frequencies, divisible by the frequency of the signal (which coincides with the frequency of the 1st main harmonic). All the harmonics with the number>1 are called higher harmonics, whereas the 1st one is called – the main harmonic. After reminding the mathematical properties of the signal we can maintain, that sometimes harmonics with even or odd numbers are absent at all. There phases are sometimes always equal to 0 and 180 degrees or to 90 and -90 degrees.
Fourier series are known to exist in sinus-cosinus form, sinus form, cosinus form, complex form. The choice depends on the problem solved and must be convenient for further analysis.
Fourier tranform is invented and adjusted for aperiodic signals with integrated absolute value and satisfaction of Diricle conditions. It’s worth saying, that Dirichle conditions is the necessary requirement for Fourier series too. Fourier representation of aperiodic signals is not discrete, but continious and the amplitudes are infinitely small. They play the role of the proportional coefficients.
3. List few characteristics of ROC
ans: 1. The ROC cannot contain any poles.
2. If h(t) is a finite-duration sequence, then the ROC is the entire s-plane, except possibly s=0 or |s|=∞
3. If h(t) is a right-sided sequence, then the ROC extends outward from the outermost pole in H(s). A right-sided sequence is a sequence where h(t)=0 for t<t1<∞
4.If h(t) is a left-sided sequence, then the ROC extends inward from the innermost pole in H(s)
5.If h(t) is a two-sided sequence, the ROC will be a ring in the z-plane that is bounded on the interior and exterior by a pole.