This set of Signals & Systems Questions & Answers for Exams focuses on “Properties of Systems – 5”.

1. For the system y (t) = x^{2}(t), which of the following holds true?

a) Invertible

b) Non-Invertible

c) Invertible as well as Non-Invertible in its respective domains

d) Cannot be determined

View Answer

Explanation: When we pass the signal x (t) through the system y (t), the system squares the input. Hence, inverse system should take square root, i.e.

W (t) = \(\sqrt{y (t)} = \sqrt{x^2 (t)}\) = ± x (t)

Thus, two outputs are possible, + x (t) or – x (t)

This means there is no unique output for unique input. Hence, this system is Non-Invertible.

2. For the system \( y (t) = ∑_{k=-∞}^n x(k)\), which of the following holds true?

a) Invertible

b) Non-Invertible

c) Invertible as well as Non-Invertible in its respective domains

d) Cannot be determined

View Answer

Explanation: \( y (t) = ∑_{k=-∞}^n x(k)\)

Or, y (n) = x (n) + x (n-1) + x (n-2) + …….

Or, y (n+1) = x (n+1) + x (n) + (terms after this)

Or, y (n+1) = x (n+1) + y (n)

Or, y (n+2) = x (n+2) + y (n+1)

Or, y (n) = x (n) + y (n-1)

This is an alternate form of given system equation.

∴ x (n) = y (n) – y (n-1)

Taking z-transform on both sides,

X (z) = Y (z) = (1-z-1)

\(H (z) = \frac{Y(z)}{X(z)} = \frac{1}{1-z-1}\)

Or, \(\frac{w(z)}{y(z)} \)= H

^{-1}(z) = (1-z-1)

∴ w (n) = y (n) – y (n-1)

Hence, the system is invertible.

3. For the system, y (t) = u{x (t)} which of the following holds true?

a) System is Linear, time-invariant, causal and stable

b) System is time-invariant, causal and stable

c) System is causal and stable

d) System is stable

View Answer

Explanation: Let x

_{1}(t) = v (t), then y

_{1}(t) = u {v (t)}

Let x

_{2}(t) = k v (t), then y

_{2}(t) = u {k v (t)} = k y

_{1}(t)

Hence, non-linear

y

_{1}(t) = u {v (t)}

y

_{2}(t) = u {v (t-t

_{0})} = y

_{1}(t-t

_{0})

Hence, time-invariant

Since the response at any time depends only on the excitation at time t=t

_{0}, and not on any further values, hence causal.

4. For the system, y (t) = x (t-5) – x (3-t) which of the following holds true?

a) System is Linear, time-invariant, causal and stable

b) System is time-invariant, causal and stable

c) System is Linear, time-invariant and stable

d) System is Linear, time-invariant and causal

View Answer

Explanation: y

_{1}(t) = v (t-5) – v (3-t)

y

_{2}(t) = k v (t-5) – k v (3-t) = ky

_{1}(t)

Let x

_{1}(t) = v (t), then y

_{1}(t) = v (t-5) – v (3-t)

Let x

_{2}(t) = 2w (t), then y

_{2}(t) = w (t-5)-w (3-t)

Let x

_{3}(t) = x (t) + w (t)

Then, y

_{3}(t) = y

_{1}(t) + y

_{2}(t)

Hence it is linear.

Again, y

_{1}(t) = v (t-5) – v (3-t)

∴ y

_{2}(t) = y

_{1}(t-t

_{0})

Hence, system is time-invariant

If x (t) is bounded, then, x (t-5) and x (3-t) are also bounded, so stable system.

At t=0, y (0) = x (-5)-x (3), therefore, the response at t=0 depends on the excitation at a later time t=3.

Therefore Non-Causal.

5. For the system, y (t) = x (\(\frac{t}{2}\)), which of the following holds true?

a) System is Linear, time-invariant, causal and stable

b) System is Linear and time-invariant

c) System is Linear and causal

d) System is Linear and stable

View Answer

Explanation: y

_{1}(t) = v (\(\frac{t}{2}\))

And y

_{2}(t) = k v (\(\frac{t}{2}\)) = k y

_{1}(t)

If x

_{3}= v (t) + w (t),

Then, y

_{3}(t) = v (\(\frac{t}{2}\)) + w (\(\frac{t}{2}\))

= y

_{1}(t) + y

_{2}(t)

Since, it satisfies both law of homogeneity and additivity, it is also linear.

Again, y

_{1}(t) = v (\(\frac{t}{2}\)), y

_{2}(\(\frac{t}{2}\)-t

_{0}) ≠ y (t-t

_{0}) = v (\(\frac{t-t_0}{2})\)

∴ The system is time variant.

If x (t) is bounded then y (t) is bounded, so a stable system.

At time t=-2, y (-2) = x (-1), therefore, the response at time t=-2 depends on the excitation at a later time, t=-1, so a Non-causal system.

6. For the system, y (t) = cos 2πt x (t), which of the following holds true?

a) System is Linear, time-invariant, causal and stable

b) System is time-invariant, causal and stable

c) System is Linear, causal and stable

d) System is Linear, time-invariant and stable

View Answer

Explanation: y

_{2}(t) k cos 2πt v (t) = k y

_{1}(t)

Again, x

_{3}(t) = v (t) + w (t)

So, y

_{3}(t) = cos 2πt [v (t) + w (t)] = y

_{1}(t) + y

_{2}(t)

Since, the system is both homogeneous and additive, therefore it is linear.

Again, y

_{1}(t) = cos 2πt v (t)

And y

_{2}(t) = cos 2πt (t-t

_{0}) ≠ y (t-t

_{0})

= cos [2π (t-t

_{0})] v (t-t

_{0})

∴ The system is time variant.

The response at any time t=t

_{0}, depends only on the excitation at that time and not on the excitation at any later time, so Causal system.

If x (t) is bounded then y (t) is also bounded, so a stable system.

7. For the system, y (t) = |x (t)|, which of the following holds true?

a) System is Linear, time-invariant, causal and stable

b) System is Linear, time-invariant and causal

c) System is Linear, time-invariant and stable

d) System is Linear, causal and stable

View Answer

Explanation: y

_{1}(t) = |v (t)|, y

_{2}(t) = |k v (t)|= |k|y

_{1}(t)

If k is negative, |k| y

_{1}(t) ≠k y

_{1}(t)

Since it is not homogeneous, so non-linear system.

Again, y

_{1}(t) = |v (t)|, y

_{2}(t) = |y (t-t

_{0})| = y

_{1}(t-t

_{0})

∴ System is time invariant.

The response at any time t=t

_{0}, depends only on the excitation at that time and not on the excitation at any later time, so causal system.

If x (t) is bounded then y (t) is also bounded, so stable system.

8. For the system, \(t\frac{dy (t)}{dt}\) – 8 y (t) = x (t), which of the following holds true?

a) System is Linear, time-invariant, causal and stable

b) System is Linear, time-invariant and causal

c) System is time-invariant, causal and stable

d) System is Linear, causal and stable

View Answer

Explanation: All options are linear. Hence linearity is not required to be checked.

Let x

_{1}(t) = v (t), then \(t\frac{dy_1 (t)}{dt}\) – 8 y

_{1}(t) = v (t)

Let x

_{2}(t) = v (t-t

_{0})

Then, \(t\frac{dy_2 (t)}{dt}\) – 8 y

_{2}(t) = v (t-t

_{0})

The first equation can be written as (t-t

_{0}) \(t\frac{dy (t-t_0)}{dt}\) – 8 y (t-t

_{0}) = x (t-t

_{0})

This equation is not satisfied if y

_{2}(t) = y

_{1}(t-t

_{0}). Therefore y

_{2}(t) ≠ y

_{1}(t-t

_{0})

∴ System is time variant.

The response at any time t=t

_{0}, depends only on the excitation at that time and not on the excitation at any later time, so Causal system.

The response will increase without bound as time increases, so unstable system.

9. For the system, \(y (t) = \int_{-∞}^{t+3} x(t) \,dt\), which of the following holds true?

a) System is Linear, time-invariant and causal

b) System is time-invariant and causal

c) System is Linear and time-invariant

d) System is Linear and stable

View Answer

Explanation: \(y_1 (t) = \int_{-∞}^{t+3} v(t) \,dt\)

And, \(y_2 (t) = \int_{-∞}^{t+3} kv(t) \,dt\)

= \(k \int_{-∞}^{t+3} x(t) \,dt\) = k y

_{1}(t)

Now, x

_{3}(t) = v (t) + w (t)

And, y

_{3}(t) = \(\int_{-∞}^{t+3}\) [v(t) + w(t)]dt

= \(\int_{-∞}^{t+3}\)v(t) dt + \(\int_{-∞}^{t+3}\)w(t) dt

= y

_{1}(t) + y

_{2}(t)

Since, it is both homogeneous and additive, so linear system.

Again, y

_{1}(t) = \(\int_{-∞}^{t+3}\) v(t) dt

And, y

_{2}(t) = \(\int_{-∞}^{t+3}\) v(t-t

_{0}) dt

= y

_{1}(t-t

_{0})

∴ System is time invariant.

The response at any time t=t

_{0}, depends partially on the excitation at time t

_{0}< t < (t

_{0}+ 3), which are in future, so non-causal system.

The response will increase without bound as time increases, so unstable system.

10. The impulse response of a continuous time LTI system is \(H (t) = (2e^{-2t} -e^{\frac{t-100}{100}}) \,u (t)\). The system is ____________

a) Causal and stable

b) Causal but not stable

c) Stable but not causal

d) Neither causal nor stable

View Answer

Explanation: For t<0, h (t) = 0.

Therefore from the definition of causality, we can infer that the system is Causal.

Now, \(\int_{-∞}^∞ |h(t)| \,dt = ∞\)

∴ From the definition of stability, we can infer that the system is unstable.

Hence, the given system is causal but not stable.

11. The impulse response of a continuous time LTI system is H (t) = e^{-|t|}. The system is ___________

a) Causal and stable

b) Causal but not stable

c) Stable but not causal

d) Neither causal nor stable

View Answer

Explanation: For t<0,

H (t) ≠ 0

Therefore the system is not causal

Again, \(\int_{-∞}^∞ |h(t)| \,dt\) = \(\frac{1}{3}\) < ∞

∴ The system is stable.

12. The impulse response of a continuous time LTI system is H (t) = e^{-t} u (3-t). The system is __________

a) Causal and stable

b) Causal but not stable

c) Stable but not causal

d) Neither causal nor stable

View Answer

Explanation: For t<0, h (t) ≠ 0

Therefore the system is not causal.

Again, \(\int_{-∞}^∞ |h(t)| \,dt = \int_{-∞}^∞ e-t \,u(3-t) \,dt = ∞ \)

∴ System is unstable.

13. The impulse response of a continuous time LTI system is H (t) = e^{-t} u (t-2). The system is __________

a) Causal and stable

b) Causal but not stable

c) Stable but not causal

d) Neither causal nor stable

View Answer

Explanation: Since, h (t) = 0 for t<0, so the system is causal.

Again, \(\int_{-∞}^∞ |h(t)| \,dt = \int_{-∞}^∞ e-t \,u(t-2) \,dt\) < ∞

∴ The system is stable.

14. The continuous time convolution integral y(t) = cos πt [u (t+1) – u (t-1) * u(t)] is __________

a) \(\frac{sinπt}{π}\) [u (t+1) – u(t-1)]

b) \(\frac{sinπt}{π}\) u(t-1)

c) \(\frac{sinπt}{π}\) u(t+1)

d) \(\frac{sinπt}{π}\) u(t)

View Answer

Explanation: For t<-1, y (t) = 0

For t<1, y (t) = \(\int_{-1}^t cosπt \,dt = \frac{sinπt}{π}\)

For t>1, y (t) = \(\int_{-1}^t\) cos πt dt = 0

∴ y (t) = \(\frac{sinπt}{π}\) [u (t+1) – u(t-1)].

15. The continuous time convolution integral y(t) = e-3tu(t) * u(t+3) is ___________

a) \(\frac{1}{3}\)[1 – e^{-3(t+3)}] u(t+3)

b) \(\frac{1}{3}\)[1 – e^{-3(t+3)}] u(t)

c) \(\frac{1}{3}\)[1 – e^{-3t}] u(t)

d) \(\frac{1}{3}\)[1 – e^{-3t}] u(t+3)

View Answer

Explanation: For t+3<0 or t<-3, y(t)=0

For t≥-3, y (t) = \(\int_{-∞}^3 e^{-3t} \,dt\)

= \(\frac{1}{3}\)[1 – e

^{-3(t+3)}]

∴ y(t) = \(\frac{1}{3}\)[1 – e

^{-3(t+3)}] u(t+3).

**Sanfoundry Global Education & Learning Series – Signals & Systems.**

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