Inverse Systems and Deconvolution MCQ Quiz – Objective Question with Answer for Inverse Systems and Deconvolution

11. A causal system produces the output sequence y(n)={1,0.7} when excited by the input sequence x(n)={1,-0.7,0.1}, then what is the impulse response of the system function?

A. [3(0.5)n+4(0.2)n]u(n)
B. [4(0.5)n-3(0.2)n]u(n)
C. [4(0.5)n+3(0.2)n]u(n)
D. None of the mentioned

Answer: B

The system function is easily determined by taking the z-transforms of x(n) and y(n). Thus we have

H(z)=\(\frac{Y(z)}{X(z)} = \frac{1+0.7z^{-1}}{1-0.7z^{-1}+0.1z^{-2}} = \frac{1+0.7z^{-1}}{(1-0.2z^{-1})(1-0.5z^{-1})}\)

Upon applying partial fractions and applying the inverse z-transform, we get
[4(0.5)n-3(0.2)n]u(n).

 

11. The Fourier series representation of any signal x(t) is defined as ___________

A. \(\sum_{k=-\infty}^{\infty}c_k e^{j2πkF_0 t}\)

B. \(\sum_{k=0}^{\infty}c_k e^{j2πkF_0 t}\)

C. \(\sum_{k=-\infty}^{\infty}c_k e^{-j2πkF_0 t}\)

D. \(\sum_{k=-\infty}^{\infty}c_{-k} e^{j2πkF_0 t}\)

Answer: A

If the given signal is x(t) and F0 is the reciprocal of the time period of the signal and ck is the Fourier coefficient then the Fourier series representation of x(t) is given as \(\sum_{k=-\infty}^{\infty}c_k e^{j2πkF_0 t}\).

 

12. Which of the following is the equation for the Fourier series coefficient?

A. \(\frac{1}{T_p} \int_0^{t_0+T_p} x(t)e^{-j2πkF_0 t} dt\)

B. \(\frac{1}{T_p} \int_{t_0}^∞ x(t)e^{-j2πkF_0 t} dt\)

C. \(\frac{1}{T_p} \int_{t_0}^{t_0+T_p} x(t)e^{-j2πkF_0 t} dt\)

D. \(\frac{1}{T_p} \int_{t_0}^{t_0+T_p} x(t)e^{j2πkF_0 t} dt\)

Answer: C

When we apply integration to the definition of Fourier series representation, we get

ckTp=\(\int_{t_0}^{t_0+T_p} x(t)e^{-j2πkF_0 t} dt\)
=>ck=\(\frac{1}{T_p} \int_{t_0}^{t_0+T_p} x(t)e^{-j2πkF_0 t} dt\)

 

13. Which of the following is a Dirichlet condition with respect to the signal x(t)?

A. x(t) has a finite number of discontinuities in any period
B. x(t) has finite number of maxima and minima during any period
C. x(t) is absolutely integrable in any period
D. all of the mentioned

Answer: D

For any signal x(t) to be represented as Fourier series, it should satisfy the Dirichlet conditions which are x(t) has a finite number of discontinuities in any period, x(t) has a finite number of maxima, and minima during any period and x(t) is absolutely integrable in any period.

 

14. The equation x(t)=\(\sum_{k=-\infty}^{\infty}c_k e^{j2πkF_0 t}\) is known as analysis equation.
A. True
B. False

Answer: B
Since we are synthesizing the Fourier series of the signal x(t), we call it a synthesis equation, whereas the equation giving the definition of Fourier series coefficients is known as the analysis equation.

 

15. Which of the following is the Fourier series representation of the signal x(t)?

A. \(c_0+2\sum_{k=1}^{\infty}|c_k|sin(2πkF_0 t+θ_k)\)

B. \(c_0+2\sum_{k=1}^{\infty}|c_k|cos(2πkF_0 t+θ_k)\)

C. \(c_0+2\sum_{k=1}^{\infty}|c_k|tan(2πkF_0 t+θ_k)\)

D. None of the mentioned

Answer: B

In general, Fourier coefficients ck are complex valued. Moreover, it is easily shown that if the periodic signal is real, ck and c-k are complex conjugates. As a result
ck=|ck|ejθkand ck=|ck|e-jθk
Consequently, we obtain the Fourier series as

x(t)=\(c_0+2\sum_{k=1}^{\infty}|c_k|cos(2πkF_0 t+θ_k)\)

 

16. The equation x(t)=\(a_0+\sum_{k=1}^∞(a_k cos2πkF_0 t – b_k sin2πkF_0 t)\) is the representation of Fourier series.

A. True
B. False

Answer: A

cos(2πkF0 t+θk) = cos2πkF0 t.cosθk-sin2πkF0 t.sinθk
θk is a constant for a given signal.
So, the other form of Fourier series representation of the signal x(t) is

\(a_0+\sum_{k=1}^∞(a_k cos2πkF_0 t – b_k sin2πkF_0 t)\).

 

17. The equation of average power of a periodic signal x(t) is given as ___________

A. \(\sum_{k=0}^{\infty}|c_k|^2\)

B. \(\sum_{k=-\infty}^{\infty}|c_k|\)

C. \(\sum_{k=-\infty}^0|c_k|^2\)

D. \(\sum_{k=-\infty}^{\infty}|c_k|^2\)

Answer: D

The average power of a periodic signal x(t) is given as
The average power of a periodic signal x(t) is given as

\(\frac{1}{T_p} \int_{t_0}^{t_0+T_p}|x(t)|^2 dt\)

=\(\frac{1}{T_p} \int_{t_0}^{t_0+T_p}x(t).x^* (t) dt\)

=\(\frac{1}{T_p} \int_{t_0}^{t_0+T_p}x(t).\sum_{k=-\infty}^{\infty} c_k * e^{-j2πkF_0 t} dt\)

By interchanging the positions of integral and summation and by applying the integration, we get

=\(\sum_{k=-\infty}^{\infty}|c_k |^2\)

 

18. What is the spectrum that is obtained when we plot |ck |2 as a function of frequencies kF0, k=0,±1,±2..?

A. Average power spectrum
B. Energy spectrum
C. Power density spectrum
D. None of the mentioned

Answer: C

When we plot a graph of |ck|2 as a function of frequencies kF0, k=0,±1,±2… the following spectrum is obtained which is known as the Power density spectrum.

 

19. What is the spectrum that is obtained when we plot |ck| as a function of frequency?

A. Magnitude voltage spectrum
B. Phase spectrum
C. Power spectrum
D. None of the mentioned

Answer: A

We know that Fourier series coefficients are complex-valued, so we can represent ck in the following way.
ck=|ck|ejθk
When we plot |ck| as a function of frequency, the spectrum thus obtained is known as the Magnitude voltage spectrum.

 

20. What is the equation of the Fourier series coefficient ck of an non-periodic signal?

A. \(\frac{1}{T_p} \int_0^{t_0+T_p} x(t)e^{-j2πkF_0 t} dt\)

B. \(\frac{1}{T_p} \int_{-\infty}^∞ x(t)e^{-j2πkF_0 t} dt\)

C. \(\frac{1}{T_p} \int_{t_0}^{t_0+T_p} x(t)e^{-j2πkF_0 t} dt\)

D. \(\frac{1}{T_p} \int_{t_0}^{t_0+T_p} x(t)e^{j2πkF_0 t} dt\)

Answer: B

We know that, for an periodic signal, the Fourier series coefficient is

ck=\(\frac{1}{T_p} \int_{-T_p/2}^{T_p/2} x(t)e^{-j2πkF_0 t} dt\)

If we consider a signal x(t) as non-periodic, it is true that x(t)=0 for |t|>Tp/2. Consequently, the limits on the integral in the above equation can be replaced by -∞ to ∞. Hence,

ck=\(\frac{1}{T_p} \int_{-\infty}^∞ x(t)e^{-j2πkF_0 t} dt\)

 

21. Which of the following relation is correct between Fourier transform X(F) and Fourier series coefficient ck?

A. ck=X(F0/k)
B. ck= 1/TP (X(F0/k))
C. ck= 1/TP(X(kF0))
D. none of the mentioned

Answer: C

Let us consider a signal x(t) whose Fourier transform X(F) is given as

X(F)=\(\int_{-∞}^∞ x(t)e^{-j2πF_0 t}dt\)

and the Fourier series coefficient is given as

ck=\(\frac{1}{T_p} \int_{-∞}^∞ x(t)e^{-j2πkF_0 t}dt\)

By comparing the above two equations, we get

ck=\(\frac{1}{T_p} X(kF_0)\)

 

22. According to Parseval’s Theorem for non-periodic signal, \(\int_{-∞}^∞|x(t)|^2 dt\).

A. \(\int_{-∞}^∞|X(F)|^2 dt \)

B. \(\int_{-∞}^∞|X^* (F)|^2 dt \)

C. \(\int_{-∞}^∞ X(F).X^*(F) dt \)

D. All of the mentioned

Answer: D

Let x(t) be any finite energy signal with Fourier transform X(F). Its energy is

Ex=\(\int_{-∞}^∞|x(t)|^2 dt\)

which in turn, can be expressed in terms of X(F) as follows

Ex=\(\int_{-∞}^∞ x^* (t).x(t)\) dt

=\(\int_{-∞}^∞ x(t) dt[\int_{-∞}^∞X^* (F)e^{-j2πF_0 t} dt]\)

=\(\int_{-∞}^∞ X^* (F) dt[\int_{-∞}^∞ x(t)e^{-j2πF_0 t} dt] \)

\(=\int_{-∞}^∞ |X(F)|^2 dt = \int_{-∞}^∞|X^* (F)|^2 dt = \int_{-∞}^∞X(F).X^* (F) dt\)

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