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Department of University of Arkansas

ELEG 5173L Digital Processing Ch. 2 The Z-Transform

Dr. Jingxian Wu [email protected] 2 OUTLINE • The Z-Transform

• Properties

• Inverse Z-Transform

• Z-Transform of LTI system 3 Z-TRANSFORM • Bilateral Z-transform

 X (z)   x(n)z n n • Unilateral Z-transform

 X (z)   x(n)z n n0

• Z-transform: – Can simplify the analysis of discrete-time LTI systems – Analyze the system in z-domain instead of – Doesn’t have any physical meaning (the representation of discrete-time signal can be obtained through discrete-time ) – Counterpart for continuous-time systems: . 4 Z-TRANSFORM • Example: find Z-transforms – 1. x(n)   (n)

n  1  – 2. x(n)    u(n)  2  5 Z-TRANSFORM

• Example n  1  – 3. x(n)    u(n 1)  2 

• Region of convergence (ROC) 6 Z-TRANSFORM: CONVERGENCE • ROC of causal signal x(n)  nu(n)

• ROC of anti-causal signal x(n)   nu(n 1) 7 Z-TRANSFORM • Example: find the Z-transforms for the following

n n  1   1  x(n)    u(n)    u(n)  2   3 8 Z-TRANSFORM • Example: find the Z-transforms for the following signals  3n , n  2  n x(n)   1   , n  2  3 9 Z-TRANSFORM: TRANSFORM TABLE 10 Z-TRANSFORM: TRANSFORM TABLE 11 OUTLINE • The Z-Transform

• Properties

• Inverse Z-Transform

• Z-Transform of LTI system 12 PROPERTIES • Linearity – If

Zx1(n) X1(z) Zx2 (n) X 2 (z)

– Then

Za1x1(n)  a2x2(n) a1X1(z)  a2 X2 (z) 13 PROPERTIES • Time Shifting – Let x ( n ) be a causal sequence with the Z-transform X (z) – Then n0 1 n0 n0 m Zx(n  n0 ) z X (z)  z  x(m)z m0

1 n0 n0 m Zx(n  n0 ) z X (z)  z  x(m)z mn0 14 PROPERTIES • Example – Solve the difference equation with initial condition y(1)  3 1 y(n)  y(n 1)   (n) 2 15 PROPERTIES • Example – Solve the difference equation with initial condition y(1) 1 y(0) 1 2 y(n  2)  y(n 1)  y(n)  u(n) 9 16 PROPERTIES • Frequency scaling – If Zx(n) X (z) – Then Zan x(n) X (a1z) 17 PROPERTIES • Example – Find the Z-transform of x(n)  an cosnu(n) 18 PROPERTIES • Differentiation with respect to z – If Zx(n) X (z)

– Then d Znx(n) z X (z) dz 19 PROPERTIES • Example – Find the Z-transform of y(n)  n(n 1)u(n) 20 PROPERTIES • Initial value lim X (z)  x(0) z

• Final value

lim(1 z1)X (z)  x() z1 21 PROPERTIES • Example – Find the initial value and final value of the following signal. z2  2z  3 X (z)  (z 1)(z  0.5)(z2  z 1) 22 PROPERTIES • – If Zh(n) H(z) Zx(n) X (z)

– Then Zx(n) h(n) X (z)H(z) • Example – Find the convolution of the following two sequences x(n)  1,2,0,1 y(n)  1,3,1 23 PROPERTIES 24 OUTLINE • The Z-Transform

• Properties

• Inverse Z-Transform

• Z-Transform of LTI system 25 INVERSE Z-TRANSFORM • Review

z az anu(n)  nanu(n)  z  a (z  a)2

• Inverse Z-Transform by partial fraction expansion – Expand X(z) in the form of z , az , etc. z  a (z  a)2 1 1 1 A A A X (z)  X (z)   0  1  2 (z  a )(z  a ) 1 2 z z(z  a1)(z  a2 ) z z  a1 z  a2

X (z) X (z) X (z) A  z A  (z  a ) A  (z  a ) 0 z 1 1 z 2 2 z z0 za1 za2 1 z z X (z)   A0  A1  A2 z(z  a1)(z  a2 ) z  a1 z  a2 26 INVERSE Z-TRANSFORM • Example – Find the inverse Z-Transform of 1 X (z)  1  1  1  z   z   z   2  2  4  27 INVERSE Z-TRANSFORM • Solve the difference equation 3 1 y(n)  y(n 1)  y(n  2)   (n) 4 8 28 INVERSE Z-TRANSFORM • Example – Find the convolution anu(n) bnu(n) 29 INVERSE Z-TRANSFORM • Example – Find the following anu(n)  (n 1)

anu(n)  (n 1) 30 OUTLINE • The Z-Transform

• Properties

• Inverse Z-Transform

• Z-Transform of LTI system 31 LTI SYSTEM • of discrete-time LTI system – ad y(n)  x(n) h(n) Y(z)  X (z)H(z) Y (z) H(z)  X (z)

• Transfer function of discrete-time LTI system N M ak y(n  k)  bk x(n  k) k0 k0 – Z-transform on both sides: N M k k ak z Y (z)  bk z X (z) k0 k0 M k bk z k0 H (z)  N k ak z k0 32 LTI SYSTEM • Example – Let the step response of a LTI system be as follows. Find the transfer function n n 6 1  1  2  1  y(n)  u(n)    u(n)    u(n) 5 2  2  15  4  33 LTI SYSTEM • Zeros and poles

(z  z )(z  z )(z  z ) H(z)  M M 1 1 (z  pN )(z  pN 1)(z  p1)

– Zeros: z1, z2 ,, zM

– Poles: p1, p2 ,, pN • Stability – A discrete-time LTI system is stable if all the poles are inside the unit circle. – A discrete-time LTI system is unstable if at least one pole is on or outside the unit circle.

– Review: a continuous-time LTI system is stable if all the poles are on the left half plane. 34 LTI SYSTEM • Example – Consider a LTI system described by the difference equation. Find the transfer function and the zeros and poles. Is the system stable? 1 y(n)  2y(n 1)  2y(n  2)  x(n)  x(n 1) 2 35 LTI SYSTEM • Example – Find the transfer function of the system shown in the following diagram. If k = 1, is the system stable?

0.8z H (z)  (z  0.5)(z  0.8) 36 LTI SYSTEM • Matlab 2  z2 – Example H(z)  1 3z1  2z2

% numerator coefficients b = [2, 0, 1]; % denominator coefficients a = [1, 3, 2];

[r, p, k] = residuez(b, a)

r = [4.5, -3], p =[-2, -1], k = 0.5

r1 r2 4.5  3 H(z)  1  1  k  1  1  0.5 1 p1z 1 p2z 1 (2)z 1 (1)z 37 LTI SYSTEM • Matlab 2  z2 – Example (Cont’d) H(z)  1 3z1  2z2

% numerator coeffcients b = [2, 0, 1]; % denominator coefficients a = [1, 3, 2];

% partial fraction expansion [r, p, k] = residuez(b, a)

% find the zeros z = roots(b);

% plot the poles and zeros zplane(b, a);

% find the output to the system with an input x x = [2, 1, -2, 3]; y = filter(b, a, x); 38 LTI SYSTEM

• Matlab 2  z2 H(z)  – Example (multiple poles) 1 4z1  4z2 % numerator coeffcients b = [2, 0, 1]; % denominator coefficients a = [1, 4, 4];

% partial fraction expansion [r, p, k] = residuez(b, a)

r = [-0.5, 2.25], p =[-2, -2], k = 0

r1 r2  0.5 2.25 H(z)  1  1 2  1  1 2 1 p1z (1 p2z ) 1 (2)z [1 (2)z ]

az n n1 nanu(n)  h(n)  0.5(2) u(n)  2.25(n 1)(2) u(n 1) (z  a)2