Digital Signal Processing System Analysis and Design 2nd Edition
By
Paulo S. R. Diniz,
Eduardo A. B. da Silva,
Sergio L. Netto
( All Chapters Included - 100% Verified Solutions )
1
,Chapter 1
D ISCRETE - TIME SYSTEMS
1.1 (a) y(n) = (n + a)2 x(n + 4)
• Linearity:
2
H{kx (n)} = (n + a) kx (n + 4) , k ∈ R
2
= k (n + a) x (n + 4)
= kH{x (n)}
2
H{x1 (n) + x2 (n)} = (n + a) [x1 (n + 4) + x2 (n + 4)]
2 2
= (n + a) x1 (n + 4) + (n + a) x2 (n + 4)
= H{x1 (n)} + H{x2 (n)}
and therefore the system is linear.
• Time Invariance:
2
y (n − n0 ) = (n − n0 + a) x (n − n0 + 4)
2
H{x (n − n0 )} = (n + a) x (n − n0 + 4)
then y (n − n0 ) 6= H{x (n − n0 )}, and the system is time varying.
• Causality:
2
H{x1 (n)} = (n + a) x1 (n + 4)
2
H{x2 (n)} = (n + a) x2 (n + 4)
If x1 (n) = x2 (n) for n < n0 , and x1 (n0 + 3) 6= x2 (n0 +3), then for n = n0 − 1 < n0 :
2
H{x1 (n)} = (n0 − 1 + a) x1 (n0 + 3)
n=n0 −1
2
H{x2 (n)} = (n0 − 1 + a) x2 (n0 + 3)
n=n0 −1
and then H{x1 (n)} =
6 H{x2 (n)} for n < n0 . Thus, the system is noncausal.
(b) y(n) = ax(n + 1)
• Linearity:
H{kx (n)} = akx (n + 1) , k ∈ R
= kH{x (n)}
H{x1 (n) + x2 (n)} = a [x1 (n + 1) + x2 (n + 1)]
= ax1 (n + 1) + ax2 (n + 1)
= H{x1 (n)} + H{x2 (n)}
1
2
,2 CHAPTER 1. DISCRETE-TIME SYSTEMS
and therefore the system is linear.
• Time Invariance:
y (n − n0 ) = ax [(n − n0 ) + 1]
H{x (n − n0 )} = ax [(n − n0 ) + 1]
then y (n − n0 ) = H{x (n − n0 )}, and the system is time invariant.
• Causality:
H{x1 (n)} = ax1 (n + 1)
H{x2 (n)} = ax2 (n + 1)
therefore, if x1 (n) = x2 (n) for n < n0 , and x1 (n0 ) 6= x2 (n0 ), then for n = n0 − 1 < n0 :
H{x1 (n)} = ax1 (n0 − 1 + 1) = ax1 (n0 )
n=n0 −1
H{x2 (n)} = ax2 (n0 − 1 + 1) = ax2 (n0 )
n=n0 −1
and then H{x1 (n)} =
6 H{x2 (n)} for n < n0 . Thus, the system is noncausal.
(c) y(n) = x(n + 1) + x3 (n − 1)
• Linearity:
H{kx (n)} = kx (n + 1) + k 3 x3 (n − 1) , k ∈ R
kH{x (n)} = kx (n + 1) + kx3 (n − 1)
H{kx (n)} 6= kH{x (n)}
and therefore the system is nonlinear.
• Time Invariance:
y (n − n0 ) = x (n − n0 + 1) + x3 (n − n0 − 1)
H{x (n − n0 )} = x (n − n0 + 1) + x3 (n − n0 − 1)
then y (n − n0 ) = H{x (n − n0 )}, and the system is time invariant.
• Causality:
H{x1 (n)} = x1 (n + 1) + x31 (n − 1)
H{x2 (n)} = x2 (n + 1) + x32 (n − 1)
If x1 (n) = x2 (n) for n < n0 , and x1 (n0 ) 6= x2 (n0 ), then, for n = n0 − 1 < n0 :
H{x1 (n)} = x1 (n0 − 1 + 1) + x31 (n0 − 1 − 1) = x1 (n0 ) + x31 (n0 − 2)
n=n0 −1
H{x2 (n)} = x2 (n0 − 1 + 1) + x32 (n0 − 1 − 1) = x2 (n0 ) + x32 (n0 − 2)
n=n0 −1
and then H{x1 (n)} =
6 H{x2 (n)} for n < n0 . Thus, the system is noncausal.
(d) y(n) = x(n) sin(ωn)
• Linearity:
H{kx (n)} = kx (n) sin (ωn) , k ∈ R
= kH{x (n)}
H{x1 (n) + x2 (n)} = [x1 (n) + x2 (n)] sin (ωn)
= x1 (n) sin (ωn) + x2 (n) sin (ωn)
= H{x1 (n)} + H{x2 (n)}
and therefore the system is linear.
3
, 3
• Time Invariance:
y (n − n0 ) = x (n − n0 ) sin (ωn − ωn0 )
H{x (n − n0 )} = x (n − n0 ) sin (ωn)
then y (n − n0 ) 6= H{x (n − n0 )}, and the system is time varying.
• Causality:
H{x1 (n)} = x1 (n) sin (ωn)
H{x2 (n)} = x2 (n) sin (ωn)
therefore if x1 (n) = x2 (n) for n < n0 , then H{x1 (n)} = H{x2 (n)} for n < n0 . Thus, the
system is causal.
(e) y(n) = x(n) + sin(ωn)
• Linearity:
H{kx (n)} = kx (n) + sin (ωn) , k ∈ R
kH{x (n)} = k [x (n) + sin (ωn)]
= kx (n) + k sin (ωn)
H{kx (n)} 6= kH{x (n)}
and therefore the system is nonlinear.
• Time Invariance:
y (n − n0 ) = x (n − n0 ) + sin (ωn − ωn0 )
H{x (n − n0 )} = x (n − n0 ) + sin (ωn)
then y (n − n0 ) 6= H{x (n − n0 )}, and the system is time varying.
• Causality:
H{x1 (n)} = x1 (n) + sin (ωn)
H{x2 (n)} = x2 (n) + sin (ωn)
If x1 (n) = x2 (n) for n < n0 , then H{x1 (n)} = H{x2 (n)} for n < n0 . Thus, the system is
causal.
x(n)
(f) y(n) = x(n+3)
• Linearity:
kx (n)
H{kx (n)} = ,k ∈ R
kx (n + 3)
x (n)
=
x (n + 3)
x (n)
kH{x (n)} = k
x (n + 3)
H{kx (n)} 6= kH{x (n)}
and therefore the system is nonlinear.
• Time Invariance:
x (n − n0 )
y (n − n0 ) =
x (n − n0 + 3)
x (n − n0 )
H{x (n − n0 )} =
x (n − n0 + 3)
then y (n − n0 ) = H{x (n − n0 )}, and the system is time invariant.
4