a) y(n) = 2x(n-1) + x(2n)
b) y(n) = a[x(n)]2 + bx(n)- Static or Dynamic Since the system requires a previous value (n-1) to obtain the current value it needs a memory to store the previous values. Hence, a system is Dynamic.
- Causal or Non-Causal Since the system requires a future value x(2n) to obtain the current value, the system is Non-Causal.
- Linear or Non-Linear The system of linear is,
- Time Variant or Time Invariant y(n, k) = 2x(n-1-k) + x(2n - k)
- Stable or Unstable If n → ∞, input signal always remains finite thus input remains finite.
T[a1x1(n) + a2x2(n)] = a1T[x1(n)] + a2T[x2(n)]
Y3 = Y2 + Y1
Y1 = 2x1(n-1) + x1(2n)
Y2 = 2x2(n-1) + x2(2n)
L.H.S = 2[a1x1(n-1) + a2x2(n-1)] + a1x1(2n) + a2x2(2n)
R.H.S = a1[2x1(n-1) + x1(2n)] + a2[2x2(n-1) + x2(2n)]
= 2a1x1(n-1) + 2a2x2(n-1) + a1x1(2n) + a2x2(2n)
= L.H.S
Therefore, system is Linear.
= L.H.S
y(n-k) = 2x(n-k-1) + x(2(n-k))
= 2x(n-k-1) + x(2n -2k)
y(n, k) ≠ y(n-k) Therefore, System is Time Variant
The given system remains finite, ∴ System is stable
- Static or Dynamic Since the system depends only on the present value it does not need any memory to store value. Therefore, the system is Static.
- Causal or Non-Causal Since the system depends only on present values it does not depend on any future value. Therefore, the system is Causal.
- Linear or Non-Linear The system of linear is,
- Time Variant or Time Invariant y(n, k) = a[x(n-k)]2 + bx(n-k)
- Stable or Unstable If n → ∞, input signal always remains finite and input remains finite too.
T[a1x1(n) + a2x2(n)] = a1T[x1(n)] + a2T[x2(n)]
Y3 = Y2 + Y1
Y1 = a[x1(n)]2 + bx1(n)
Y2 = a[x2(n)]2 + bx2(n)
L.H.S = a{[a1[x1(n)] + a2[x2(n)]}2
R.H.S = a1{a[x1(n)]2 + bx1} + a2{a[x2(n)]2 + bx2}
=aa1[x1(n)]2 + bx1(n) + aa2[x2(n)]2 + bx2(n)
= a{a1[x1(n)]2 + a2[x2(n)]2} + b[a1x1(n) + a2x2(n)]
≠ L.H.S
Therefore, system is Non-Linear.
= a{a1[x1(n)]2 + a2[x2(n)]2} + b[a1x1(n) + a2x2(n)]
≠ L.H.S
y(n-k) = a[x(n-k)]2 + bx(n-k)
y(n, k) = y(n-k)
Therefore, System is Time Invariant.
The given system remains finite, ∴ System is stable