Scaling Property MCQ Quiz - Objective Question with Answer for Scaling Property - Download Free PDF

Last updated on Jul 9, 2025

Latest Scaling Property MCQ Objective Questions

Scaling Property Question 1:

Which type of property is shown by the following function.

L{K f(t)} = K F(s)

  1. Shifting theorem 
  2. Scaling theorem
  3. Linearity
  4. Distribution theorem

Answer (Detailed Solution Below)

Option 3 : Linearity

Scaling Property Question 1 Detailed Solution

Concept:

The property shown by the function L{K f(t)} = K F(s) is Linearity.

Here's a brief explanation of why:

  • Linearity: The linearity property of the Laplace Transform states that for constants 'a' and 'b', and functions f(t) and g(t) with Laplace Transforms F(s) and G(s) respectively, the transform of a linear combination is the linear combination of their transforms: L{a f(t) + b g(t)} = a F(s) + b G(s) The given expression L{K f(t)} = K F(s) is a specific instance of this linearity, showing that a constant multiplier can be factored out of the transform.

Time shifting

x(t - t0)  ↔  e-jωto. X(ω)

Frequency shifting

ejωt . x(t) ↔ X (ω - ω0)

Time scaling

Time Reversal

x(-t) ↔ X (-ω)

Scaling Property Question 2:

The magnitude of Fourier transform X(ω) of a function x(t) is shown below in figure (a). The magnitude of Fourier transform Y(ω) of another function y(t) is shown in figure (b). The phases of X(ω) and Y(ω) are zero for all ω. The magnitude and frequency units are identical in both the figures. The function y(t) can expressed in terms of x(t) as

Answer (Detailed Solution Below)

Option 4 :

Scaling Property Question 2 Detailed Solution

We know that, expansion in frequency domain result in compression in the time domain and vice versa.

In the given question, compression is done frequency domain. So there will be expansion in time domain by same amount.

A x(t/2) ↔ 2A X(2f)

2A = 3 ⇒ A = 3/2

Top Scaling Property MCQ Objective Questions

Which type of property is shown by the following function.

L{K f(t)} = K F(s)

  1. Shifting theorem 
  2. Scaling theorem
  3. Linearity
  4. Distribution theorem

Answer (Detailed Solution Below)

Option 3 : Linearity

Scaling Property Question 3 Detailed Solution

Download Solution PDF

Concept:

The property shown by the function L{K f(t)} = K F(s) is Linearity.

Here's a brief explanation of why:

  • Linearity: The linearity property of the Laplace Transform states that for constants 'a' and 'b', and functions f(t) and g(t) with Laplace Transforms F(s) and G(s) respectively, the transform of a linear combination is the linear combination of their transforms: L{a f(t) + b g(t)} = a F(s) + b G(s) The given expression L{K f(t)} = K F(s) is a specific instance of this linearity, showing that a constant multiplier can be factored out of the transform.

Time shifting

x(t - t0)  ↔  e-jωto. X(ω)

Frequency shifting

ejωt . x(t) ↔ X (ω - ω0)

Time scaling

Time Reversal

x(-t) ↔ X (-ω)

The magnitude of Fourier transform X(ω) of a function x(t) is shown below in figure (a). The magnitude of Fourier transform Y(ω) of another function y(t) is shown in figure (b). The phases of X(ω) and Y(ω) are zero for all ω. The magnitude and frequency units are identical in both the figures. The function y(t) can expressed in terms of x(t) as

Answer (Detailed Solution Below)

Option 4 :

Scaling Property Question 4 Detailed Solution

Download Solution PDF

We know that, expansion in frequency domain result in compression in the time domain and vice versa.

In the given question, compression is done frequency domain. So there will be expansion in time domain by same amount.

A x(t/2) ↔ 2A X(2f)

2A = 3 ⇒ A = 3/2

Scaling Property Question 5:

Which type of property is shown by the following function.

L{K f(t)} = K F(s)

  1. Shifting theorem 
  2. Scaling theorem
  3. Linearity
  4. Distribution theorem

Answer (Detailed Solution Below)

Option 3 : Linearity

Scaling Property Question 5 Detailed Solution

Concept:

The property shown by the function L{K f(t)} = K F(s) is Linearity.

Here's a brief explanation of why:

  • Linearity: The linearity property of the Laplace Transform states that for constants 'a' and 'b', and functions f(t) and g(t) with Laplace Transforms F(s) and G(s) respectively, the transform of a linear combination is the linear combination of their transforms: L{a f(t) + b g(t)} = a F(s) + b G(s) The given expression L{K f(t)} = K F(s) is a specific instance of this linearity, showing that a constant multiplier can be factored out of the transform.

Time shifting

x(t - t0)  ↔  e-jωto. X(ω)

Frequency shifting

ejωt . x(t) ↔ X (ω - ω0)

Time scaling

Time Reversal

x(-t) ↔ X (-ω)

Scaling Property Question 6:

Let  be Wide Sense Stationary random process with power spectral density . If  is a random process defined as , the power spectral density  is:

Answer (Detailed Solution Below)

Option 3 :

Scaling Property Question 6 Detailed Solution

Power density has no effect of shifting. It is affected only by scaling

We know,

 

and 

Now, 

then using the scaling property of Fourier transforms we have,

Thus, the power spectral density of  is .

Scaling Property Question 7:

The magnitude of Fourier transform X(ω) of a function x(t) is shown below in figure (a). The magnitude of Fourier transform Y(ω) of another function y(t) is shown in figure (b). The phases of X(ω) and Y(ω) are zero for all ω. The magnitude and frequency units are identical in both the figures. The function y(t) can expressed in terms of x(t) as

Answer (Detailed Solution Below)

Option 4 :

Scaling Property Question 7 Detailed Solution

We know that, expansion in frequency domain result in compression in the time domain and vice versa.

In the given question, compression is done frequency domain. So there will be expansion in time domain by same amount.

A x(t/2) ↔ 2A X(2f)

2A = 3 ⇒ A = 3/2

Scaling Property Question 8:

Let x(t) X(jω) be Fourier Transform pair. The Fourier Transform of the signal x(5t-3) in terms of X(jω) is given as

Answer (Detailed Solution Below)

Option 1 :

Scaling Property Question 8 Detailed Solution

using the properties of fourier transform

                 Time shift                          x(t) --> X(jw)                           x(t-to) --> x(jw)

                  Time scaling                    x(t) --> X(jw)                            x(at) -->

                    We get                                 

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