This set of Signals & Systems Multiple Choice Questions & Answers (MCQs) focuses on “Properties of Systems – I”.
1. Is the system y(t) = Rx(t), where R is a arbitrary constant, a memoryless system?
Explanation: The output of the system depends on the input of the system at the same time instant. Hence, the system has to be memoryless.
2. Does the following discrete system have the parameter of memory, y[n] = x[n-1] + x[n] ?
Explanation: y[n] depends upon x[n-1], i.e at the earlier time instant, thus forcing the system to have memory.
3. y[t]= ∫x[t],t ranges from 0 to t. Is the system a memoryless one?
d) Both memoryless and having memory
Explanation: While evaluating the integral, it becomes imperative to know the values of x[t] from 0 to t, thus making the system requiring memory.
4. y(t) = sin(x(t-1)) : Comment on its memory aspects.
a) Having memory
b) Needn’t have memory
c) Memoryless system
d) Time invariant system
Explanation: The output at any time t = A, requires knowing the input at an earlier time, t = A – 1, hence making the system require memory aspects.
5. Construct the inverse system of y(t) = 2x(t)
a) y(t) = 0.5x(t)
b) y(t) = 2x(t)
c) y(2t) = x(t)
d) y(t) = x(2t)
Explanation: Now, y(t) = 2x(t) => x(t) = 0.5*y(t)
Thus, reversing x(t) <-> y(t), we obtain the inverse system: y(t) = 0.5x(t)
6. y(t) = x^2(t). Is y(t) = sqrt(x(t)) the inverse of the first system?
d) Inverse doesn’t exist.
Explanation: We cannot determine the sign of the input from the second function, thus, the output doesn’t replicate the input. Thus, the second function is not an inverse of the first one.
7. Comment on the causality of y[n] = x[-n]
a) Time invariant
c) Non causal
d) Time varying
Explanation: For positive time, the system may seem to be causal. However, for negative time, the output depends on time at a positive sign, thus being in the future, enforcing non causality.
8. y(t) = x(t-2) + x(2-t). Comment on its causality:
b) Time variant
c) Non causal
Explanation: For a time instant existing between 0 and 1, it would depend on the input at a time in the future as well, hence being non causal.
9. Comment on the causality of y[n] = n*x[n] a) Time invariant
b) Time varying
c) Non causal
Explanation: For positive time, the system may seem to be causal. For negative time, the output depends on the same time instant, thus making it causal.
10. Comment on the linearity of y[n] = n*x[n]
b) Only additive
c) Not scalable
d) Non linear
Explanation: The function obeys the scaling/homogeneity property, but doesn’t obey the additivity property, thus not being linear.
Sanfoundry Global Education & Learning Series – Signals and Systems.