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ECE 308 -11

Z Transform Rational Z-Transform The inverse of the z-transform

Z. Aliyazicioglu

Electrical and Computer Engineering Department Cal Poly Pomona

Rational Z-Transform

Poles and Zeros The poles of a z-transform are the values of z for which if X(z)=∞ The zeros of a z-transform are the values of z for which if X(z)=0

X(z) is in rational form

M −k −−1 M ∑bzk Nz() bbz01+++... bzMk= 0 Xz()==−−1 N =M Dz( ) a01+++ az ... aN z −k ∑azk k=0 Nz() b ( z − zzz)( −−)...( zz) Xz()==0 z−+MN 12 M D()z a012()()() zpzp−− ... zp −N M z − z ∏()k M finite zeros at z = zz12, ,..., zM Nz() NM− k=1 Xz()== Gz N Dz() N finite poles at zpp= , ,..., p ∏()z − pk 12 N k=1 And |N-M| zeros if N>M or poles if M>N at the origin z=0 ECE 307-11 2

1 Rational Z-Transform

Poles and Zeros

We can represent X(z) graphically by a pole-zero plot in complex plane. Shows the location of poles by (x) Shows the location of zeros by (o). Definition of ROC of a z-transform should not contain any poles.

Example: Determine the pole-zero plot for the signal n x()naun= () Im(z) 1 z The z-transform is Xz()== 1− az−1 z− a Re(z) o ax One zero at z1=0 0

One pole at p1=a . p1=a is not included in the ROC ECE 307-11 3

Rational Z-Transform

Example.2: Determine the pole-zero plot for the signal

 ann 07≤ ≤ xn()=  a > 0 0elsewhere

8 ,. … 7 −1 88 The z-transform is n 1− (az ) za− Xz() az−1 ==∑() −17 = n=0 1− az z() z− a (zz− )( zz−−)...( zz) Xz()= 12 7 z7 Im(z) j2/π kM The zeros j2/8π j4/8π zaek = zae= zae= o 1 2 o o zae= j14π /8 a Re(z) the poles at p=0 7 o x o 0 o o ROC: the entire z-plane except z=0 o ECE 307-11 4

2 Rational Z-Transform

Pole Location and Time-Domain behavior for Causal Signals

n For the signal x()naun= () a > 0 x(n) 0

One zero at z1=0 . One pole at p1=a. x(n)

The signal is decaying 01 The signal is fixed if a=1 n The signal is growing if a>1 The signal alternates if a is negative Im(z)

Causal signals with poles outside the 0 a Re(z) unit circle become unbounded. o x

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Rational Z-Transform

Pole Location and Time-Domain behavior for Causal Signals

Impulse invariance mapping is z = e s T Im{s} 1 1 Im{z} fmax = ⇒ fs > 1 2π π

Re{s} Re{z} -1 1 1

-1

s = -1 ± j ⇒ z = 0.198 ± j 0.31 (T = 1 s) s = 1 ± j ⇒ z = 1.469 ± j 2.287 (T = 1 s) s = j 2 π f Laplace Domain Z Domain Left-hand plane Inside unit circle Imaginary axis Unit circle Right-hand plane Outside unit circle

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3 Rational Z-Transform

The system Function of a Linear Time –Invariant System

The input sequence x(n) The output sequence y(n) The relationship in the z-domain Yz()= HzXz () ()

Yz() H(z) is obtained Hz()= is called system function X ()z

∞ H ()zhnz= ∑ ()−n We can take the inverse of z-transform to find h(n). n=−∞ H(z) can be obtained from a linear constant-coefficient difference equation.

NN yn()=−∑∑ aynkkk () − + bxnk () − kk==10 ECE 307-11 7

Rational Z-Transform

H(z) can be obtained from a linear constant-coefficient difference equation.

NN yn()=−∑∑ aynkkk () − + bxnk () − kk==10 The z-transform

,,, NN −kk− Yz()=−∑∑ aYzzkk () + bXzz () kk==10

NN −kk− Yz()1+=∑∑ azkk bXzz () kk==10

N bz−k Yz() ∑ k Hz()==k=0 N Xz() −k 1+ ∑azk k=1

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4 Rational Z-Transform

1 Example: yn()=−+ yn ( 1)2() xn 2 The z-transform from the difference equation 1 Yz()=+ Yzz ()−1 2 Xz () 2 The system function Yz() 2 Hz()== 1 Xz() 1− z−1 2 The system has one pole at and one zero at The inverse z-transform

n 1 hn()= 2 un () 2

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The inverse of the z-transform

The inverse z-transform is formally given by

1 x()nXzzdz= ()n−1 2π j v∫C

There are three methods for evaluation of inverse z- transform 1. Direct evaluation by Contour integration (using Cauchy residue theorem) 2. Expansion into a series of term in the and 3. Partial- expansion and table lookup.

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5 The inverse of the z-transform

The Inverse z-transform by Power Series Expansion

∞ −n With given ROC: X ()zcz= ∑ n n=−∞

Example: Using Power Series Expansion to determine the inverse z-transform of

1 >> y=[1]; Xz()= 11.5− zz−12+ 0.5− >> h=[1 –1.5 0.5]; >> n=7; a. ROC: z >1 >> y=[y zeros(1,n-1)]; //y={1,0,0,0,0,0,0} b. ROC: z < 0.5 >> [x,r]=deconv(y,h) x = 1.0000 1.5000 1.7500 1.8750 1.9375 1.9688 r = 0 0 0 0 0 0 1.9844 -0.9844 x(0)== 1,xx (1) 1.5, (2) = 1.75, x (3) = 1.875, x (4) = 1.9375ECE 307-11 11

The inverse of the z-transform a. Since the ROC is the exterior of the circle, we can expect x(n) to be a causal. 371531 1...+++zzzz−−12 − 3 + − 4 + 24 816 31 11−+zz−−12 22 31 1−+zz−−12 22 31 Therefore . zz−−12− 22 3 7 15 31 Xzzzzz( )= 1+++−−12 − 3 + − 4 + ..... 393 zzz−−−123−+ 24 816 244 73 zz−−23− x(n) con be obtained as 44 7217 371531 zzz−−−234−+ xn( )= {1, , , , ,.....} 488 24 816 15 7 zz−−34− ↑ 88 15 45 15 zzz−345−+−− 81616 31 15 zz−45− − 16 16 ECE 307-11 12

6 The inverse of the z-transform b. ROC is the interior of a circle. The signal x(n) is anticausal. The long division in the following way.

26430...zzz234+++ z 5 + 13 zz−−21−+11 22 13−+zz 22 2 32zz− Therefore, 39zz−+23 6 z Xz( )= 2 z23++ 6 z 14 z 4 + 30 z 5 + ..... 76zz23− 72114zzz234−+ x(n) can be obtained as 15zz34− 14 x(n )= {...30,14,6,2,0,0} 15zzz345−+ 45 30 31zz45− 30 ↑

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The inverse of the z-transform

The inverse z-transform by Partial Fraction Expansion

We usually have X(z) function in a rational function form

−−1 M Nz() bbz01+++... bzM Xz()== −−1 N Dz() a01+++ az ... aN z A rational function is called proper if M

−12311−− 1 Example: 13++z zz + 1 −1 63 z Xz()= Xz()=+ 1 2 z−1 + 6 51−−12 51 1++zz 1++zz−12− 66 66 ECE 307-11 14

7 The inverse of the z-transform

The inverse z-transform by Partial Fraction Expansion

Find the poles (denominator roots). We can have distinct real poles, distinct complex poles, multiple-order real poles, and multiple-order complex poles.

Distinct Poles: The poles are all different

AA12 AN Xz()=+++−11−− ... 1 11−−pz12 pz 1 − pN z

We can determine coefficient using different methods. Let’s give an example and use the of the methods

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The inverse of the z-transform

Example: Determine the partial fraction expansion the following function 1 Xz()= 11.5− zz−12+ 0.5−

1 AA Xz()==+12 (1−− 1zzz−−−111 )(1 0.5 ) 1 − 1 1 − 0.5 z − 1

To find coefficients 11 AzXz=−(1 1−1 ) ( ) = = = 2 1 zz−−11==11(1−− 0.5z−1 ) 1 0.5 11 AzXz=−(1 0.5−1 ) ( ) = = =− 1 2 zz−−11==22(1−−z−1 ) 1 2

We have Assume that signal is causal From the z-transform table 21 Xz()=−−11− n 110.5−−zz x()nun=− 2 (0.5) () ECE 307-11 16

8 The inverse of the z-transform

Using MatLab to find inverse z-transform

>> syms z n >> iztrans(1/(1-1.5*z^-1+0.5*z^-2)) ans = 2-(1/2)^n

>> syms z n >> ztrans(2-(1/2)^n) ans = 2*z/(z-1)-2*z/(2*z-1)

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The inverse of the z-transform

Multiple – order poles:

If X(z) has repeated poles. This time we use a different expansion. Let’s say D(z) contains a repeated poles (1 − pz − 1 ) r . Then Nz() Xz()= −1 r (1− pz ) D1 ( z ) −−+−+121rr AAzAzAzNz12rr− 1 1() =+−−112111 +++... −−−rr + (1)(1)(1)(1)()−−pzpzpzpzDz − − 1

To find A12,,...,AAr

1()dzNzrr−−11 dzNzr−1 () A = A = 11r−1 −1 21−1 z = z = (1)!rdzDz− 1 () p dz D1() z p

zNzr−1 () Ar = 1 z−1 = Dz1() p ECE 307-11 18

9 The inverse of the z-transform

Example:

1 1 AAAz−1 Xz()= Xz()==++123 (1+−zz−−112 )(1 ) (1+−zzzzz−−−−−1121 )(1 ) (1 + ) (1 − 1 ) (1 − 12 )

Determine the coefficients. A12,,andAA 3 11 AzXz=+(1−1 ) ( ) = = 1 zz−−11=−11(1− z−12 ) =− 4 z 1 AzzXz=−(1−12 ) ( ) = = 3 zz−−11==11(1+ z−1 ) 2

d AzzXz=−(1−12 ) ( ) 2 dz z−1 =1 dz+−−+(1 zzz−−12 ) ( ) 2 1 3 = === −−1122z−1 =1 dz(1++ z )z−1 =1 (1 z ) 2 4

−1 11 31 1z 131n Xz()=++ x()nnun=−++ (1) () 4(1+−−zzz−−−1112 ) 4(1 ) 2(1 ) 442

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The inverse of the z-transform

Distinct complex poles Example 1+ z −1 Xz()= Find inverse z-transform. 10.5− z−12+ z− Partial Fraction Xz() 1++ z−−11 1 z ==−−11 zpzpz(1−−12 )(1 )  11−−11  11  11−+jz −−  jz   22  22  AA =+12 11−−11  11 11−+jz −−  jz 22  22 Determine the coefficients. 1 1+ 11 −1 + j −1 113+ z 22 A11=−(1pz ) X ( z ) zp= = 1 = =− j 1 z−1 = 11−1 11 22 1−−jz + j 22 22 11 1   1−−j 2211 + j 22ECE 307-11 20

10 The inverse of the z-transform

Example (cont)

1 1+ 11 −1 − j −1 113+ z 22 A22=−(1pz ) X ( z ) zp= = 1 = =+ j 2 z−1 = 11−1 11 22 1−+jz − j 22 22 11 1   1−+j 2211 − j 22 13 13 −1 −+jj 1+ z 22 22 Xz()==−−12 + 10.5−+zz 11−−11  11  11−+jz −−  jz   22  22 

1310 1310 Aj=− = e− j71.565 Aj=+ = e+ j71.565 A = A* 1 222 2 222 12

111+ jπ /4 pj1 =+ = e * 22 2 p12= p ECE 307-11 21

The inverse of the z-transform

Example (cont)

10− jj71.565 10 71.565 1+ z−1 ee Xz()==22 + 10.5−+zz−−12 11  11−−ezjjππ/4−−− 1 e /4 z 1  22  Inverse z-transform.

nn 10−−jj71.565 1ππ / 4 10 j 71.565  1 j / 4  x()ne=+ eune ()  eun  () 2222  

n ππnn  11jj−−−71.565 1  71.565 x()neeun=+ 1044  ()  2 22

n 1 π n x(nun )=− 10 cos 71.565 ( ) 2 4

>> n=0:20; >> x=sqrt(10)*(1/sqrt(2)).^n.*cos(pi*n/4-0.397*pi); >> stem(n,x) ECE 307-11 22

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