Correct Answer - Option 2 : linear and non-causal
Concept:
Causal: A system is said to be causal if a system is dependent on present or past inputs only but not on the future input.
Linear: A system is said to be linear if it follows both superposition and homogeneity.
y{ax1[t] + bx2[t]} = a y{x1[t]} + b y{x2[t]}
Conditions to check whether the system is linear or not:
1) The output should be zero for zero input.
2) There should not be any non-linear operator present in the system.
Application:
y(t) = x(2t) + x(3t)
The given system is not causal because, for positive values of time, the output is depending upon the future values of the input.
Example: For t = 1, the output is:
y(1) = x(2) + x(3)
The given system is linear because:
1) For zero input, the output is also zero
2) It satisfies both additivity and homogeneity property, i.e.
y{ax1[t] + bx2[t]} = a y{x1[t]} + b y{x2[t]}