Monday, 14 November 2016

Signals and Vectors

Signals and Vectors
1. Define Signal.
A. Signal is a physical quantity that varies with respect to time , space or any other independent variable.
Or
It is a mathematical representation of the system. Eg y(t) = t. and x(t)= sin t.

2. Define system?
A. A set of components that are connected together to perform the particular task.

3. What are the major classifications of the signal?
A. (i) Discrete time signal
    (ii) Continuous time signal

4. Define discrete time signals and classify them.
A. Discrete time signals are defined only at discrete times, and for these signals, the
independent variable takes on only a discrete set of values.
Classification of discrete time signal:
1.Periodic and Aperiodic signal
2.Even and Odd signal

5. Define continuous time signals and classify them.
A. Continuous time signals are defined for a continuous of values of the independent variable. In the case of continuous time signals the independent variable is continuous.
For example:
(i) A speech signal as a function of time
(ii) Atmospheric pressure as a function of altitude
Classification of continuous time signal:
(i) Periodic and Aperiodic signal
(ii) Even and Odd signal

6. Define discrete time unit step &unit impulse.
A. Discrete time Unit impulse is defined as   δ[n]=   {0, n≠ 0
{1, n=0
Unit impulse is also known as unit sample.
Discrete time unit step signal is defined by
U[n]=              {0,n=0
{1,n>= 0

7. Define continuous time unit step and unit impulse.
A. Continuous time unit impulse is defined as
δ(t)=    {1, t=0
{0, t ≠ 0
Continuous time Unit step signal is defined as
U(t)=               {0, t<0
{1, t≥0

8. Define unit ramp signal.
A. Continuous time unit ramp function is defined by
r(t)=                 {0,t<0
{t, t≥0
A ramp signal starts at t=0 and increases linearly with time ‘t’.

9. Define periodic signal. and nonperiodic signal.
A. A signal is said to be periodic ,if it exhibits periodicity.i.e., X(t +T)=x(t), for all values of t. Periodic signal has the property that it is unchanged by a time shift of T. A signal that does not satisfy the above periodicity property is called an aperiodic signal.

10. Define even and odd signal ?
A. A discrete time signal is said to be even when,     x[-n]=x[n].
The continuous time signal is said to be even when,  x(-t)= x(t)
For example,Cosωn is an even signal.
The discrete time signal is said to be odd when         x[-n]= -x[n]
The continuous time signal is said to be odd when    x(-t)= -x(t)
Odd signals are also known as nonsymmetrical signal.
Sine wave signal is an odd signal.

11. Define Energy and power signal.
A. A signal is said to be energy signal if it have finite energy and zero power.
A signal is said to be power signal if it have infinite energy and finite power.
If the above two conditions are not satisfied then the signal is said to be neither energy nor power signal

12. Define unit pulse function.
A. Unit pulse function Π(t) is obtained from unit step signals
Π(t)=u(t+1/2)- u(t-1/2)
The signals u(t+1/2) and u(t-1/2) are the unit step signals shifted by 1/2units in the time axis towards the left and right ,respectively.

13. Define continuous time complex exponential signal.
A. The continuous time complex exponential signal is of the form
x(t)=Ceat
where c and a are complex numbers.

14. What is continuous time real exponential signal.
A. Continuous time real exponential signal is defined by
x(t)=Ceat          where c and a are complex numbers. If c and a are real, then it is called as real exponential.

15. What is continuous time growing exponential signal?
A. Continuous time growing exponential signal is defined as
x(t)=Ceat          where c and a are complex numbers. If a is positive, as t increases, then x(t) is a growing exponential.

16. What is continuous time decaying exponential?
A. Continuous time growing exponential signal is defined as
x(t)=Ceat          where c and a are complex numbers. If a is negative, as t increases, then x(t) is a decaying exponential.

17. Check Whether the given system is causal and stable.
A. y ( n ) = 3 x ( n - 2) + 3 x ( n + 2 )
Since y (n) depends upon x(n+2), this system is noncausal. As long as x (n – 2) and
x(n + 2) are bounded, the output y(n) will be bounded. Hence this system is stable.

18. What is the periodicity of x(t) = ej100Πt + 30 ?
A. Here x(t) = ej100Πt + 30
Comparing above equation with ejωt+Ф, we get ω = 100 Π. Therefore period T is given as,
T=2 Π/ ω = 2 Π /100 Π = 1/50 = 0.02 sec.

19. Find the fundamental period of the signal x(n)= 3 ej3Π(n+1/2)
A. X(n) = 3/5 ej3Πn.      ej3Π/2  = -j3/5 ej3Πn
Here, ω=3Π, hence, f=3/2=k/N. Thus the fundamental period is N = 2.
20. Is the discrete time system describe by the equation y (n) = x(-n) causal or non causal ?
Why?
A. Here y(n) = x(-n). If n = -2 then, y(-2 )= x(2). Thus the output depends upon future inputs. Hence system is noncausal.

21. Is the system describe by the equation y(t) = x(2t) Time invariant or not? Why?
A. Output for delayed inputs becomes,y(t,t1) =x(2t-t1).       Delayed output will be,                      y(t-t1) = x[2(t-t1)].            Since y(t,t1) ≠ y(t-t1) . The system is shift variant.

22. What is analogy between vector and signal?
A vector of the kind used in geometrical applications can be used to indicate a time-varying sinusoidal signal or a fixed two dimensional image or a three dimensional point. But when a signal, such as arising from a vibration or a seismic signal or even a voice signal, is to be represented.
The analogy between the sets of points of the signal and the vector of points is now clear. The purpose of visualizing such an analogy is to mathematically perform such operations on the signal which would convert the signal information in a more useful form. A filter which operates on the signal does it. A Fourier transform which operates on the vector of data tells the frequencies present in the signal.
23. Give an example to show analogy between vector and signal
A. Nuclear magnetic resonance of a chemical, dichloro-ethane from such a spectrometer instrument.
24. What are ‘Orthogonal’ functions?
A. The sine and cosine functions belong to this category. We can therefore represent a signal as a sum of a number of sine and cosine waves sin θ, sin 2θ, sin 3θ... cos θ, cos 2θ, cos 3θ... etc. Here θ denotes the time variable, by the usual θ = ωt relationship.
25. Advantage of orthogonality?
A. Advantage of orthogonal functions is the coefficients are independent and so, if a fit has been made with an mth-degree polynomial in P, and it is decided later to use a higher degree, giving more terms, only the additional coefficients are required to be calculated and those already calculated remain unchanged.
26. What is purpose of Fourier series?
A. Used to analyze periodic signals, harmonic constant of signals is analyzed and it can be developed for continuous time as well as discrete time signals.

27. What are the types of Fourier series?
A.        1. Exponential Fourier series
2. Trigonometric Fourier series

28.Write down the exponential form of the Fourier series representation of a periodic signal?
A. The equation is given by,
Here the summation is taken from -  to
Here the integration is taken from 0 to T. The set of coefficients { X(k)} are often called the Fourier series coefficients or spectral coefficients. The coefficient ao is the dc or constant component of x(t).

29.Write short notes on dirichlets conditions for fourier series.

A. a. x(t) must be absolutely integrable
b. The function x(t) should be single valued within the interval T.
c. The function x(t) should have finite number of discontinuities in any
finite interval of time T.
d. The function x(t) should have finite number of maxima &minima in the
interval T.

30. What do odd functions have in Fourier series?
A. It has only Sine terms. i.e., b(k) 
33. Which terms will be left for a even function  in Fourier series?
A. It consists of only cosine terms. i.e., a(k)   
34. Explain half symmetry.
A. Signal x(t) is said to be half symmetry if   x(t) = - x(t ± T/2)        
            a(0) = 0 and a(k) = b(k) = 0 for even ‘k’
a(k) =    for ‘k’ odd
b(k) =    for ‘k’ even;              a(k) and b(k) contain only odd harmonics


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