dea.brunel.ac.uk cmsp home saeed vaseghi chapter04-z-transform

5/21/2018 Dea.brunel.ac.Uk Cmsp Home Saeed Vaseghi Chapter04-Z-Transform

4

z-Transform

4.1 Introduction4.2 z-Transform4.3 The Z-Plane and the Unit Circle4.4 Properties of the z-transform4.5 Transfer Function, Poles and Zeroes4.6 Physical Interpretation of Poles and Zeroes4.7 The Inverse z-transform

-transform, like the Laplace transform, is an indispensable mathematical toolfor the design, analysis and monitoring of systems. The z-transform is the

discrete-time counter-part of the Laplace transform and a generalisation of theFourier transform of a sampled signal. Like Laplace transform the z-transform

allows insight into the transient behaviour, the steady state behaviour, and the stabilityof discrete-time systems. A working knowledge of the z-transform is essential to thestudy of digital filters and systems. This chapter begins with the definition of theLaplace transform and the derivation of the z-transform from the Laplace transform ofa discrete-time signal. A useful aspect of the Laplace and the z-transforms are therepresentation of a system in terms of the locations of the poles and the zeros of thesystem transfer function in a complex plane. In this chapter we derive the so-called z-plane, and its associated unit circle, from sampling the s-plane of the Laplacetransform. We study the description of a system in terms the system transfer function.The roots of the transfer function, the so-called poles and zeros of transfer function,provide useful insight into the behaviour of a system. Several examples illustrating thephysical significance of poles and zeros and their effect on the impulse and frequencyresponse of a system are considered.

x(mk)x(m) z kZ Z

Z

Z

Z

Z

ZZ

Z

Z Z

Z


Sec. 4.1 Introduction2

4.1 Introduction

The Laplace transform and its discrete-time counterpart the z-transform are essentialmathematical tools for system design and analysis, and for monitoring the stability ofa system. A working knowledge of the z-transform is essential to the study of discrete-time filters and systems. It is through the use of these transforms that we formulate aclosed-form mathematical description of a system in the frequency domain, design thesystem, and then analyse the stability, the transient response and the steady statecharacteristics of the system.A mathematical description of the input-output relation of a system can be formulatedeither in the time domain or in the frequency domain. Time-domain and frequencydomain representation methods offer alternative insights into a system, and depending

on the application it may be more convenient to use one method in preference to theother. Time domain system analysis methods are based on differential equations whichdescribe the system output as a weighted combination of the differentials (i.e. the ratesof change) of the system input and output signals. Frequency domain methods, mainlythe Laplace transform, the Fourier transform, and the z-transform, describe a system interms of its response to the individual frequency constituents of the input signal. Insection 4.?? we explore the close relationship between the Laplace, the Fourier and thez-transforms, and the we observe that all these transforms employ various forms ofcomplex exponential as their basis functions. The description of a system in thefrequency domain can reveal valuable insight into the system behaviour and stability.System analysis in frequency domain can also be more convenient as differentiationand integration operations are performed through multiplication and division by thefrequency variable respectively. Furthermore the transient and the steady state

characteristics of a system can be predicted by analysing the roots of the Laplacetransform or the z-transform, the so-called poles and zeros of a system.

4.2 Derivation of the z-Transform

The z-transform is the discrete-time counterpart of the Laplace transform. In thissection we derive the z-transform from the Laplace transform a discrete-time signal.The Laplace transformX(s), of a continuous-time signalx(t), is given by the integral

=0

)()( dtetxsX st

(4.1)


Chap. 4 z-Transform 3

where the complex variables= +j, and the lower limit of t=0allows the possibility

that the signal x(t) may include an impulse. The inverse Laplace transform is defined

by

+

=j

j

stdsesXtx1

1

)()(

(4.2)

where 1 is selected so that X(s) is analytic (no singularities) for s>1. The z-transform can be derived from Eq. (4.1) by sampling the continuous-time input signal

x(t). For a sampled signal x(mTs), normally denoted as x(m) assuming the sampling

period Ts=1, the Laplace transform Eq. (4.1) becomes

=

=0

)()(m

sms emxeX (4.3)

Substituting the variable se in Eq. (4.3) with the variablezwe obtain the one-sided z-

transform equation

=

=0

)()(m

mzmxzX (4.4)

The two-sided z-transform is defined as

=

=m

mzmxzX )()( (4.5)

Note that for a one-sided signal,x(m)=0 for m


Sec 4.2 Derivation of the z-Transform4

of the Fourier transform of a continuous-time signal, and the z-transform is ageneralisation of the Fourier transform of a discrete-time signal. In the previoussection we have shown that the z-transform can be derived as the Laplace transform ofa discrete-time signal. In the following we explore the relation between the z-transform and the Fourier transform. Using the relationship

fs reeeez 2jj === (4.6)

m

rmIm[ej2mf]

m m

rmIm[ej2mf] rmIm[ej2mf]

r< 1 r=1 r>1

Figure 4.1 Thez-transform basis functions.

where

s=+jand =2f, we can rewrite the z-transform Eq. (4.4) in the followingform

=

=0

2j)()(m

mfmermxzX (4.7)

Note that when r =e=1 the z-transform becomes the Fourier transform of a sampledsignal given by

=

==m

fmf emxezX 2j2j )()( (4.8)

Therefore the z-transform is a generalisation of the Fourier transform of a sampledsignal derived in sec. 3.xx. Like the Laplace transform, the basis functions for the z-

transform are damped or growing sinusoids of the formfmmm

erz2j

= as shown inFig. 4.1. These signals are particularly suitable for transient signal analysis. TheFourier basis functions are steady complex exponential, fme 2j , of time-invariant

amplitudes and phase, suitable for steady state or time-invariant signal analysis.



A similar relationship exists between the Laplace transform and the Fourier transformof a continuous time signal. The Laplace transform is a one-sided transform with the

lower limit of integration at = 0t , whereas the Fourier transform Eq. (3.21) is a two-sided transform with the lower limit of integration at =t . However for a one-sided

signal, which is zero-valued for < 0t , the limits of integration for the Laplace andthe Fourier transforms are identical. In that case if the variable s in the Laplace

transform is replaced with the frequency variable j2f then the Laplace integralbecomes the Fourier integral. Hence for a one-sided signal, the Fourier transform is a

special case of the Laplace transform corresponding tos=j2f and =0.

Example 4.1 Show that the Laplace transform of a sampled signal is periodic with

respect to the frequency axis jof the complex frequency variables= +j.

Solution: In Eq. (4.3) substitute s+jk2, where k is an integer variable, for thefrequency variablesto obtain

)()(

)()()(1

2j)2j(2j

s

m

sm

m

mksm

m

mksks

eXemx

eemxemxeX

==

==

=

= =

=

++321

(4.9)

Hence the Laplace transform of a sample signal is periodic with a period of 2 as

shown in Fig. 4.2.a

4.3 The z-Plane and The Unit Circle

The frequency variables of the Laplace transform s= +j, and the z-tranformz=rej

are complex variables with real and imaginary parts and can be visualised in a twodimensional plane. Figs. 4.2.a and 4.2.b shows the s-plane of the Laplace transform

and the z-plane of z-transform. In the s-plane the vertical jaxis is the frequencyaxis, and the horizontal -axis gives the exponential rate of decay, or the rate ofgrowth, of the amplitude of the complex sinusoid as also shown in Fig. 4.1. As shown


Sec 4.3 The z-plane, The Unit Circle6

.

.

.

Z-Plane

The unit circle corresponds

to the jaxis of the s-plan,

it is the location of the Fourier

basis functions

Outside the unit circle

corresponds to >0 part

of the s-plane

Inside the unit circle

corresponds to the 1,is mapped onto the outside of the unit circle this is the region of unstable signals and

systems. The jaxis, with =0 or r =e=1,is itself mapped onto the unit circle line.Hence the cartesian co-ordinates used in s-plane for continuous time signals Fig. 4.2.a,is mapped into a polar representation in the z-plane for discrete-time signals Fig 4.2.b.

Fig. 4.3 illustrates that an angle of 2,i.e. once round the unit circle, corresponds to afrequency of FsHz where Fs is the sampling frequency. Hence a frequency of fHz

corresponds to an anglegiven by

fFs

2= radians (4.10)

For example at a sampling rate of Fs=40 kHz, a frequency of 5 kHz corresponds to an

angle of 25/40= 0.05 radians or 45 degrees.



Z-Plane

Re

Im

0 Hz

FsHz

Fs/4 Hz

Fs/2 Hz

3Fs/4 Hz

Figure 4.3 -Illustration of mapping a frequency of fHz to an angle of radians.

4.3.1 The Region of Convergence (ROC)

Since the z-transform is an infinite power series, it exists only for those values of thevariablezfor which the series converges to a finite sum. The region of convergence(ROC) ofX(z) is the set of all the values ofz for whichX(z) attains a finite computablevalue.

Example 4.2 Determine the z-transform, the region of convergence, and the Fouriertransform of the following signal

===

00

01)()(

m

mmmx (4.11)

Solution:Substituting forx(m) in the z-transform Eq. (4.4) we obtain

x(m)

m



1)0()()( 0 ====

zzmxzXm

m (4.12)

For all values of the variable zwe haveX(z)=1, hence asshown in the shaded area of the left hand side figure theregion of convergence is the entire z-plane.The Fourier transform of x(m) may be obtained by

evaluatingX(z) in Eq. (4.12) at jez= as

1)( j =eX (4.13)

Example 4.3 Determine thez-transform, the region of convergence, and the Fouriertransform of the following signal

===

km

kmkmmx

0

1)()( (4.14)

Solution: Substituting forx(m) in the z-transform Eq. (4.4) we obtain

k

m

mzzkmzX

=

== )()( (4.15)

The z-transform is kk zzzX /1)( == . Hence X(z) isfinite-valued for all the values of z except for z=0. Asshown by the shaded area of the left hand side figure, theregion of convergence is the entire z-plane except thepoint z=0. The Fourier transform is obtained by

evaluatingX(z) in Eq. (4.15) at jez= as

kjeeX

j)( = (4.16)

Re

Im

x(m)

mk

Re

Im




==+=

km

kmkmmx

0

1)()( (4.17)


k

m

m zzmxzX ==

=

)()( (4.18)

The z-transform is kzzX =)( . Hence X(z) is finite-valued for all the values of z except for =z . Asshown by the shaded area of the left hand side figure,the region of convergence is the entire z-plane except

the point =z which is not shown. The Fouriertransform is obtained by evaluating X(z) in Eq. (4.18)

at jez= as

keeX jj )( = (4.19)


==++=

km

kmkmkmmx

0

1)()()( (4.20)

x(m)

m-k

Re

Im

x(m)

m-k k




kk

m

m zzzmxzX

=

+== )()( (4.21)

Thez-transform is HenceX(z)is finite-valued for all thevalues of zexcept for z=0 and =z . As shown by theshaded area of the left hand side figure, the region ofconvergence is the entire z-plane except the points z=0and =z not shown. The Fourier transform is obtainedby evaluating Eq. (4.21) at jez= as

)cos(2)( jjj keeeX kk =+= + (4.22)

Example 4.6 Determine thez-transform and region of convergence of

x m m

m

m

( ) =

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socalled zplane