SlideShare a Scribd company logo
1 of 17
Download to read offline
EC533: Digital Signal Processing
  5          l      l

             Lecture 6
The Z-Transform and its application in
          signal processing
6.1 - Z-Transform and LTI System
                                                                          ∞
 • S t
   System Function of LTI Systems:
          F ti      f LTI S t                               h (n ) = ∑ h (n )z − n
                   x(n )
                                                                     n = −∞
                                  h(n )        y (n )
                                                                          Y (z )
                   X (z )         H (z )        Y (z )         H (z ) =
                                                                          X (z )
• As the LTI system can be characterized by the difference equation, written as




• The diffe ence equation specifies the actual operation that must be performed by
   he difference                               ope ation              pe fo med
the discrete-time system on the input data, in the time domain, in order to generate
the desired output.
  In Z domain
     Z-domain

   If the O/p of the system depends only on the present & past I/p samples but not
on previous outputs, i.e., bk=0’s FIR system, Else, Infinite Impulse Response
                              0s
(IIR)
6.1.1 - LTI System Transfer Function


  If the O/p of the system depends only on the present & past i/p samples but not
on previous outputs i.e., bk=0’s
            outputs, i e     0s     Finite Impulse Response (FIR) system ,
                                    Finite Impulse Response (FIR) system
             H (z ) = ∑ a k z − k
                           N

                        k =0           h(n) = 0, n < 0, h(n) = 0, n >N,
 FIR system is an all zero system and are always stable



 If bk≠0’s, the system is called Infinite Impulse Response (IIR) system
                                                               IIR filter has poles

                  h( n)
                      ),       -∞ ≤ n ≤ ∞
6.1.2 - Properties of LTI Systems Using the Z-
                       Transform
Causal Systems : ROC extends outward from the outermost pole.
                                                      Im



                                                                    R
                                                                    Re



Stable Systems (H(z) is BIBO): ROC includes the unit circle.
                                                               Im
A stable system requires that its Fourier transform is
uniformly convergent.                                           1
                                                                    Re
6.2 - Z-transform and Frequency Response
                                   Estimation
• The frequency response of a system (as digital filter spectrum) can be readily obtained
from its z-transform.

                                                                        H(z)
                                                                        H( )
 as,
 where σ is a transient term & it tends to zero as f
     at steady state,                                   Steady‐state frequency response of 
                                                        a system (DTFT).



  where, A(ω)≡ Amplitude (Magnitude) Response , B(ω) ≡ Angle (Phase) Response




                                       Steady‐state
6.2 - Frequency Response Estimation – cont.

• Phase Delay
The amount of time delay, each frequency component of the signal suffers in
                    delay
going through the system.




• Group Delay
The average time delay the composite signal suffers at each frequency.
6.3 - Inverse Z-Transform

                               where
                        DTFT

             IDTFT




                                 (A contour integral)


where, for a fixed r,
6.3 - The Inverse Z-Transform – cont.
•   There is an inversion integral for the z transform,

                              1
                     x[n ] =       X(z)z n−1dz
                             j2π ∫
                                 C


    but doing it requires integration in the complex plane and
    it is rarely used in engineering practice.


•   There are two other common methods,

        Power series method (long division method)
        Partial-Fraction Expansion
                           p
6.3.1 - Power Series (Long Division) Method
Suppose it is desired to find the inverse z transform of
                   z2
              z3 −
H(z ) =            2
           15 2 17     1
        z − z + z−
         3

           12      36 18
Synthetically dividing the numerator by the
denominator yields the infinite series
d     i t      i ld th i fi it     i
         3 −1 67 −2
     1+ z +          z +L
         4      144
This will always work but the answer is not
in closed form (Disadvantage).
6.3.2 - Partial-Fraction Expansion

•Put H(z-1) in a fractional form with the degree of numerator less than degree of
 denominator.
•Put the denominator in the form of simple poles.
• A l partial fraction expansion.
  Apply   i lf     i         i
• Apply inverse z transform for those simple fractions.

                                           Note
                 If N: order of numerator, & M: order of denominator.
                 then,

                 If N=M     Divide

                 If 1N<M 
                 If 1N<M     Make direct P.F.
                             Make direct P F

                 If N>M     Make long division then P.F.
Example 1:

find,       a) Transfer Function   b) Impulse Response




                                        -1     -1/3      7/3




                                   *3
                                    3


        3         3                 3
Example 2:
 Consider the discrete system,

a)
 )      Determine the poles & zeros.
        D            h     l
b)      Plot (locate) them on the z-plane.
c)      Discuss the stability.
d)      Find the impulse response.
e)      Find the first 4 samples of h(n)

     Solution:

     a) zeros when N(z)=0                                       b)
         z1=2        z2= - 0.5
         poles when D(z)=0                                                    xo x          o
                                                                                      0.3   2
         p1=0.3     p2= - 0.6

                                                                      ‐ 0.6   ‐ 0.5

     c) Since all poles lies inside the unit circle, therefore the system is stable.
Example 2 – cont.
d) As discussed before, use partial fraction expansion and the table of transformation to
    get the inverse z-transform
c) Divide N(z) by D(z) using long division,
 )           () y ()        g    g         ,




                                      1

                                          1 2 3

                                                    ‐ 0.24
                                           ‐ 0.28

                                      ‐ 1.8
Example 3:
 Consider the system described by the following difference equation,


Find,
a) The transfer function.
b) Th steady state frequency response.
      The t d t t f
c) The O/p of the system when a sine wave of frequency 50 Hz & amplitude of 10 is
      applied at its input, the sampling frequency is 1 KHz.

   Solution:
               a)
Example 3– cont.
 b)
Example 3– cont.
c)   x(n) = A sin(ω0 nT + θ )
                                1
          = 10 sin((2π .50.n.      ) + θ ) = 10 sin(0.1πn)
                              1000
     Since the I/p is sinusoidal, the O/p should be sinusoidal,
     y (n) = Ay sin(0.1πn + θ y )
     where, A = A A(ω )
              y    x    0

               θ y = θ x + θ (ω0 )
                                                1
     Ay = 10 ×
                 1 − (0.5 cos(ω0T )) 2 + (0.5 sin(ω0T )) 2
                              10
          =                                             = 18.3
            1 − (0.5 cos(0.1π )) 2 + (0.5 sin(0.1π )) 2
                     ⎛ 0.5 sin(0.1π ) ⎞
     θ y = θ x − tan ⎜     −1
                                          ⎟ = 1780 24′
                     ⎜ 1 − 0.5 cos(0.1π ) ⎟
                     ⎝                    ⎠
6.4 Relationships between System
           Representations
              p


Express H(z) in
   1/z cross                      H(z)                 Take inverse z-
 multiply and                                             transform
 take inverse     Take z-transform            Take
                   solve for Y/X         z-transform
          Difference
                                                         h(n)
           Equation        Substitute
                            z=ejwT
                                         Take inverse
                                             DTFT

      Take DTFT solve            H(ejwT)
                                                   Take Fourier
          for Y/X
                                                    transform

More Related Content

What's hot

Chapter4 - The Continuous-Time Fourier Transform
Chapter4 - The Continuous-Time Fourier TransformChapter4 - The Continuous-Time Fourier Transform
Chapter4 - The Continuous-Time Fourier TransformAttaporn Ninsuwan
 
Laplace transform & fourier series
Laplace transform & fourier seriesLaplace transform & fourier series
Laplace transform & fourier seriesvaibhav tailor
 
Dsp U Lec10 DFT And FFT
Dsp U   Lec10  DFT And  FFTDsp U   Lec10  DFT And  FFT
Dsp U Lec10 DFT And FFTtaha25
 
discrete time signals and systems
 discrete time signals and systems  discrete time signals and systems
discrete time signals and systems Zlatan Ahmadovic
 
Digital Signal Processing[ECEG-3171]-Ch1_L03
Digital Signal Processing[ECEG-3171]-Ch1_L03Digital Signal Processing[ECEG-3171]-Ch1_L03
Digital Signal Processing[ECEG-3171]-Ch1_L03Rediet Moges
 
DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)
DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)
DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)Amr E. Mohamed
 
Circular Convolution
Circular ConvolutionCircular Convolution
Circular ConvolutionSarang Joshi
 
Z TRANSFORM PROPERTIES AND INVERSE Z TRANSFORM
Z TRANSFORM PROPERTIES AND INVERSE Z TRANSFORMZ TRANSFORM PROPERTIES AND INVERSE Z TRANSFORM
Z TRANSFORM PROPERTIES AND INVERSE Z TRANSFORMTowfeeq Umar
 
Chapter5 - The Discrete-Time Fourier Transform
Chapter5 - The Discrete-Time Fourier TransformChapter5 - The Discrete-Time Fourier Transform
Chapter5 - The Discrete-Time Fourier TransformAttaporn Ninsuwan
 
Laplace transformation
Laplace transformationLaplace transformation
Laplace transformationWasim Shah
 
Z transforms and their applications
Z transforms and their applicationsZ transforms and their applications
Z transforms and their applicationsRam Kumar K R
 
Discrete Fourier Transform
Discrete Fourier TransformDiscrete Fourier Transform
Discrete Fourier TransformShahryar Ali
 
Signals and Systems Formula Sheet
Signals and Systems Formula SheetSignals and Systems Formula Sheet
Signals and Systems Formula SheetHaris Hassan
 
Z Transform And Inverse Z Transform - Signal And Systems
Z Transform And Inverse Z Transform - Signal And SystemsZ Transform And Inverse Z Transform - Signal And Systems
Z Transform And Inverse Z Transform - Signal And SystemsMr. RahüL YøGi
 
Convolution discrete and continuous time-difference equaion and system proper...
Convolution discrete and continuous time-difference equaion and system proper...Convolution discrete and continuous time-difference equaion and system proper...
Convolution discrete and continuous time-difference equaion and system proper...Vinod Sharma
 

What's hot (20)

Lecture9
Lecture9Lecture9
Lecture9
 
Z transform
Z transformZ transform
Z transform
 
Chapter4 - The Continuous-Time Fourier Transform
Chapter4 - The Continuous-Time Fourier TransformChapter4 - The Continuous-Time Fourier Transform
Chapter4 - The Continuous-Time Fourier Transform
 
Laplace transform & fourier series
Laplace transform & fourier seriesLaplace transform & fourier series
Laplace transform & fourier series
 
Dsp U Lec10 DFT And FFT
Dsp U   Lec10  DFT And  FFTDsp U   Lec10  DFT And  FFT
Dsp U Lec10 DFT And FFT
 
discrete time signals and systems
 discrete time signals and systems  discrete time signals and systems
discrete time signals and systems
 
Digital Signal Processing[ECEG-3171]-Ch1_L03
Digital Signal Processing[ECEG-3171]-Ch1_L03Digital Signal Processing[ECEG-3171]-Ch1_L03
Digital Signal Processing[ECEG-3171]-Ch1_L03
 
DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)
DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)
DSP_FOEHU - MATLAB 04 - The Discrete Fourier Transform (DFT)
 
Circular Convolution
Circular ConvolutionCircular Convolution
Circular Convolution
 
Z TRANSFORM PROPERTIES AND INVERSE Z TRANSFORM
Z TRANSFORM PROPERTIES AND INVERSE Z TRANSFORMZ TRANSFORM PROPERTIES AND INVERSE Z TRANSFORM
Z TRANSFORM PROPERTIES AND INVERSE Z TRANSFORM
 
Chapter5 - The Discrete-Time Fourier Transform
Chapter5 - The Discrete-Time Fourier TransformChapter5 - The Discrete-Time Fourier Transform
Chapter5 - The Discrete-Time Fourier Transform
 
z transforms
z transformsz transforms
z transforms
 
Z TRRANSFORM
Z  TRRANSFORMZ  TRRANSFORM
Z TRRANSFORM
 
Z Transform
Z TransformZ Transform
Z Transform
 
Laplace transformation
Laplace transformationLaplace transformation
Laplace transformation
 
Z transforms and their applications
Z transforms and their applicationsZ transforms and their applications
Z transforms and their applications
 
Discrete Fourier Transform
Discrete Fourier TransformDiscrete Fourier Transform
Discrete Fourier Transform
 
Signals and Systems Formula Sheet
Signals and Systems Formula SheetSignals and Systems Formula Sheet
Signals and Systems Formula Sheet
 
Z Transform And Inverse Z Transform - Signal And Systems
Z Transform And Inverse Z Transform - Signal And SystemsZ Transform And Inverse Z Transform - Signal And Systems
Z Transform And Inverse Z Transform - Signal And Systems
 
Convolution discrete and continuous time-difference equaion and system proper...
Convolution discrete and continuous time-difference equaion and system proper...Convolution discrete and continuous time-difference equaion and system proper...
Convolution discrete and continuous time-difference equaion and system proper...
 

Viewers also liked

Dsp U Lec05 The Z Transform
Dsp U   Lec05 The Z TransformDsp U   Lec05 The Z Transform
Dsp U Lec05 The Z Transformtaha25
 
Dsp U Lec04 Discrete Time Signals & Systems
Dsp U   Lec04 Discrete Time Signals & SystemsDsp U   Lec04 Discrete Time Signals & Systems
Dsp U Lec04 Discrete Time Signals & Systemstaha25
 
Dsp U Lec07 Realization Of Discrete Time Systems
Dsp U   Lec07 Realization Of Discrete Time SystemsDsp U   Lec07 Realization Of Discrete Time Systems
Dsp U Lec07 Realization Of Discrete Time Systemstaha25
 
Dsp U Lec01 Real Time Dsp Systems
Dsp U   Lec01 Real Time Dsp SystemsDsp U   Lec01 Real Time Dsp Systems
Dsp U Lec01 Real Time Dsp Systemstaha25
 
Digital Signal Processing Tutorial:Chapt 2 z transform
Digital Signal Processing Tutorial:Chapt 2 z transformDigital Signal Processing Tutorial:Chapt 2 z transform
Digital Signal Processing Tutorial:Chapt 2 z transformChandrashekhar Padole
 
Dsp U Lec02 Data Converters
Dsp U   Lec02 Data ConvertersDsp U   Lec02 Data Converters
Dsp U Lec02 Data Converterstaha25
 
Dsp U Lec03 Analogue To Digital Converters
Dsp U   Lec03 Analogue To Digital ConvertersDsp U   Lec03 Analogue To Digital Converters
Dsp U Lec03 Analogue To Digital Converterstaha25
 
Dsp U Lec09 Iir Filter Design
Dsp U   Lec09 Iir Filter DesignDsp U   Lec09 Iir Filter Design
Dsp U Lec09 Iir Filter Designtaha25
 
Applications of Z transform
Applications of Z transformApplications of Z transform
Applications of Z transformAakankshaR
 
3F3 – Digital Signal Processing (DSP) - Part1
3F3 – Digital Signal Processing (DSP) - Part13F3 – Digital Signal Processing (DSP) - Part1
3F3 – Digital Signal Processing (DSP) - Part1op205
 
Digital Implementation of Costas Loop with Carrier Recovery
Digital Implementation of Costas Loop with Carrier RecoveryDigital Implementation of Costas Loop with Carrier Recovery
Digital Implementation of Costas Loop with Carrier RecoveryIJERD Editor
 
Neural nets: How regular expressions brought about deep learning
Neural nets: How regular expressions brought about deep learningNeural nets: How regular expressions brought about deep learning
Neural nets: How regular expressions brought about deep learningMatthew
 
Documents.mx polytronics
Documents.mx polytronicsDocuments.mx polytronics
Documents.mx polytronicsPOWER EEE
 

Viewers also liked (20)

Dsp U Lec05 The Z Transform
Dsp U   Lec05 The Z TransformDsp U   Lec05 The Z Transform
Dsp U Lec05 The Z Transform
 
Dsp U Lec04 Discrete Time Signals & Systems
Dsp U   Lec04 Discrete Time Signals & SystemsDsp U   Lec04 Discrete Time Signals & Systems
Dsp U Lec04 Discrete Time Signals & Systems
 
Z transform
 Z transform Z transform
Z transform
 
Dsp U Lec07 Realization Of Discrete Time Systems
Dsp U   Lec07 Realization Of Discrete Time SystemsDsp U   Lec07 Realization Of Discrete Time Systems
Dsp U Lec07 Realization Of Discrete Time Systems
 
Dsp U Lec01 Real Time Dsp Systems
Dsp U   Lec01 Real Time Dsp SystemsDsp U   Lec01 Real Time Dsp Systems
Dsp U Lec01 Real Time Dsp Systems
 
Digital Signal Processing Tutorial:Chapt 2 z transform
Digital Signal Processing Tutorial:Chapt 2 z transformDigital Signal Processing Tutorial:Chapt 2 z transform
Digital Signal Processing Tutorial:Chapt 2 z transform
 
Dsp U Lec02 Data Converters
Dsp U   Lec02 Data ConvertersDsp U   Lec02 Data Converters
Dsp U Lec02 Data Converters
 
Dsp U Lec03 Analogue To Digital Converters
Dsp U   Lec03 Analogue To Digital ConvertersDsp U   Lec03 Analogue To Digital Converters
Dsp U Lec03 Analogue To Digital Converters
 
Dsp U Lec09 Iir Filter Design
Dsp U   Lec09 Iir Filter DesignDsp U   Lec09 Iir Filter Design
Dsp U Lec09 Iir Filter Design
 
Applications of Z transform
Applications of Z transformApplications of Z transform
Applications of Z transform
 
3F3 – Digital Signal Processing (DSP) - Part1
3F3 – Digital Signal Processing (DSP) - Part13F3 – Digital Signal Processing (DSP) - Part1
3F3 – Digital Signal Processing (DSP) - Part1
 
Digital Implementation of Costas Loop with Carrier Recovery
Digital Implementation of Costas Loop with Carrier RecoveryDigital Implementation of Costas Loop with Carrier Recovery
Digital Implementation of Costas Loop with Carrier Recovery
 
Dsp iit workshop
Dsp iit workshopDsp iit workshop
Dsp iit workshop
 
Neural nets: How regular expressions brought about deep learning
Neural nets: How regular expressions brought about deep learningNeural nets: How regular expressions brought about deep learning
Neural nets: How regular expressions brought about deep learning
 
One sided z transform
One sided z transformOne sided z transform
One sided z transform
 
Chapter5 system analysis
Chapter5 system analysisChapter5 system analysis
Chapter5 system analysis
 
Documents.mx polytronics
Documents.mx polytronicsDocuments.mx polytronics
Documents.mx polytronics
 
Impulse response
Impulse responseImpulse response
Impulse response
 
inverse z transform
inverse z transforminverse z transform
inverse z transform
 
Lab no.07
Lab no.07Lab no.07
Lab no.07
 

Similar to Dsp U Lec06 The Z Transform And Its Application

Z-transform and Its Inverse.ppt
Z-transform and Its Inverse.pptZ-transform and Its Inverse.ppt
Z-transform and Its Inverse.pptNahi20
 
A Novel Methodology for Designing Linear Phase IIR Filters
A Novel Methodology for Designing Linear Phase IIR FiltersA Novel Methodology for Designing Linear Phase IIR Filters
A Novel Methodology for Designing Linear Phase IIR FiltersIDES Editor
 
Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)IJERD Editor
 
An Intuitive Approach to Fourier Optics
An Intuitive Approach to Fourier OpticsAn Intuitive Approach to Fourier Optics
An Intuitive Approach to Fourier Opticsjose0055
 
Generating Chebychev Chaotic Sequence
Generating Chebychev Chaotic SequenceGenerating Chebychev Chaotic Sequence
Generating Chebychev Chaotic SequenceCheng-An Yang
 
Intelligent Process Control Using Neural Fuzzy Techniques ~陳奇中教授演講投影片
Intelligent Process Control Using Neural Fuzzy Techniques ~陳奇中教授演講投影片Intelligent Process Control Using Neural Fuzzy Techniques ~陳奇中教授演講投影片
Intelligent Process Control Using Neural Fuzzy Techniques ~陳奇中教授演講投影片Chyi-Tsong Chen
 
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...ijceronline
 
Dsp U Lec08 Fir Filter Design
Dsp U   Lec08 Fir Filter DesignDsp U   Lec08 Fir Filter Design
Dsp U Lec08 Fir Filter Designtaha25
 
ADSP (17 Nov)week8.ppt
ADSP (17 Nov)week8.pptADSP (17 Nov)week8.ppt
ADSP (17 Nov)week8.pptAhmadZafar60
 
EC8553 Discrete time signal processing
EC8553 Discrete time signal processing EC8553 Discrete time signal processing
EC8553 Discrete time signal processing ssuser2797e4
 
Circuit Network Analysis - [Chapter5] Transfer function, frequency response, ...
Circuit Network Analysis - [Chapter5] Transfer function, frequency response, ...Circuit Network Analysis - [Chapter5] Transfer function, frequency response, ...
Circuit Network Analysis - [Chapter5] Transfer function, frequency response, ...Simen Li
 
ch6_digital_filters.pptx
ch6_digital_filters.pptxch6_digital_filters.pptx
ch6_digital_filters.pptxKadiriIbrahim2
 

Similar to Dsp U Lec06 The Z Transform And Its Application (20)

Z-transform and Its Inverse.ppt
Z-transform and Its Inverse.pptZ-transform and Its Inverse.ppt
Z-transform and Its Inverse.ppt
 
A Novel Methodology for Designing Linear Phase IIR Filters
A Novel Methodology for Designing Linear Phase IIR FiltersA Novel Methodology for Designing Linear Phase IIR Filters
A Novel Methodology for Designing Linear Phase IIR Filters
 
Final
FinalFinal
Final
 
Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)Welcome to International Journal of Engineering Research and Development (IJERD)
Welcome to International Journal of Engineering Research and Development (IJERD)
 
Rdnd2008
Rdnd2008Rdnd2008
Rdnd2008
 
Adc
AdcAdc
Adc
 
An Intuitive Approach to Fourier Optics
An Intuitive Approach to Fourier OpticsAn Intuitive Approach to Fourier Optics
An Intuitive Approach to Fourier Optics
 
Dsp 2marks
Dsp 2marksDsp 2marks
Dsp 2marks
 
Generating Chebychev Chaotic Sequence
Generating Chebychev Chaotic SequenceGenerating Chebychev Chaotic Sequence
Generating Chebychev Chaotic Sequence
 
Intelligent Process Control Using Neural Fuzzy Techniques ~陳奇中教授演講投影片
Intelligent Process Control Using Neural Fuzzy Techniques ~陳奇中教授演講投影片Intelligent Process Control Using Neural Fuzzy Techniques ~陳奇中教授演講投影片
Intelligent Process Control Using Neural Fuzzy Techniques ~陳奇中教授演講投影片
 
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...IJCER (www.ijceronline.com) International Journal of computational Engineerin...
IJCER (www.ijceronline.com) International Journal of computational Engineerin...
 
ADSP (17 Nov).ppt
ADSP (17 Nov).pptADSP (17 Nov).ppt
ADSP (17 Nov).ppt
 
Dsp U Lec08 Fir Filter Design
Dsp U   Lec08 Fir Filter DesignDsp U   Lec08 Fir Filter Design
Dsp U Lec08 Fir Filter Design
 
ADSP (17 Nov)week8.ppt
ADSP (17 Nov)week8.pptADSP (17 Nov)week8.ppt
ADSP (17 Nov)week8.ppt
 
Signal Processing Homework Help
Signal Processing Homework HelpSignal Processing Homework Help
Signal Processing Homework Help
 
Chapter 5
Chapter 5Chapter 5
Chapter 5
 
EC8553 Discrete time signal processing
EC8553 Discrete time signal processing EC8553 Discrete time signal processing
EC8553 Discrete time signal processing
 
Circuit Network Analysis - [Chapter5] Transfer function, frequency response, ...
Circuit Network Analysis - [Chapter5] Transfer function, frequency response, ...Circuit Network Analysis - [Chapter5] Transfer function, frequency response, ...
Circuit Network Analysis - [Chapter5] Transfer function, frequency response, ...
 
Introduction to chaos
Introduction to chaosIntroduction to chaos
Introduction to chaos
 
ch6_digital_filters.pptx
ch6_digital_filters.pptxch6_digital_filters.pptx
ch6_digital_filters.pptx
 

Recently uploaded

🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘RTylerCroy
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationSafe Software
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking MenDelhi Call girls
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Drew Madelung
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonAnna Loughnan Colquhoun
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...Neo4j
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Scriptwesley chun
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsJoaquim Jorge
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking MenDelhi Call girls
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityPrincipled Technologies
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Servicegiselly40
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationRadu Cotescu
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEarley Information Science
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoffsammart93
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?Antenna Manufacturer Coco
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slidevu2urc
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024The Digital Insurer
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerThousandEyes
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherRemote DBA Services
 

Recently uploaded (20)

🐬 The future of MySQL is Postgres 🐘
🐬  The future of MySQL is Postgres   🐘🐬  The future of MySQL is Postgres   🐘
🐬 The future of MySQL is Postgres 🐘
 
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time AutomationFrom Event to Action: Accelerate Your Decision Making with Real-Time Automation
From Event to Action: Accelerate Your Decision Making with Real-Time Automation
 
08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men08448380779 Call Girls In Civil Lines Women Seeking Men
08448380779 Call Girls In Civil Lines Women Seeking Men
 
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
Strategies for Unlocking Knowledge Management in Microsoft 365 in the Copilot...
 
Data Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt RobisonData Cloud, More than a CDP by Matt Robison
Data Cloud, More than a CDP by Matt Robison
 
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...Workshop - Best of Both Worlds_ Combine  KG and Vector search for  enhanced R...
Workshop - Best of Both Worlds_ Combine KG and Vector search for enhanced R...
 
Automating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps ScriptAutomating Google Workspace (GWS) & more with Apps Script
Automating Google Workspace (GWS) & more with Apps Script
 
Artificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and MythsArtificial Intelligence: Facts and Myths
Artificial Intelligence: Facts and Myths
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men08448380779 Call Girls In Greater Kailash - I Women Seeking Men
08448380779 Call Girls In Greater Kailash - I Women Seeking Men
 
Boost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivityBoost PC performance: How more available memory can improve productivity
Boost PC performance: How more available memory can improve productivity
 
CNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of ServiceCNv6 Instructor Chapter 6 Quality of Service
CNv6 Instructor Chapter 6 Quality of Service
 
Scaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organizationScaling API-first – The story of a global engineering organization
Scaling API-first – The story of a global engineering organization
 
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptxEIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
EIS-Webinar-Prompt-Knowledge-Eng-2024-04-08.pptx
 
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot TakeoffStrategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
Strategize a Smooth Tenant-to-tenant Migration and Copilot Takeoff
 
What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?What Are The Drone Anti-jamming Systems Technology?
What Are The Drone Anti-jamming Systems Technology?
 
Histor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slideHistor y of HAM Radio presentation slide
Histor y of HAM Radio presentation slide
 
Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024Partners Life - Insurer Innovation Award 2024
Partners Life - Insurer Innovation Award 2024
 
How to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected WorkerHow to Troubleshoot Apps for the Modern Connected Worker
How to Troubleshoot Apps for the Modern Connected Worker
 
Strategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a FresherStrategies for Landing an Oracle DBA Job as a Fresher
Strategies for Landing an Oracle DBA Job as a Fresher
 

Dsp U Lec06 The Z Transform And Its Application

  • 1. EC533: Digital Signal Processing 5 l l Lecture 6 The Z-Transform and its application in signal processing
  • 2. 6.1 - Z-Transform and LTI System ∞ • S t System Function of LTI Systems: F ti f LTI S t h (n ) = ∑ h (n )z − n x(n ) n = −∞ h(n ) y (n ) Y (z ) X (z ) H (z ) Y (z ) H (z ) = X (z ) • As the LTI system can be characterized by the difference equation, written as • The diffe ence equation specifies the actual operation that must be performed by he difference ope ation pe fo med the discrete-time system on the input data, in the time domain, in order to generate the desired output. In Z domain Z-domain If the O/p of the system depends only on the present & past I/p samples but not on previous outputs, i.e., bk=0’s FIR system, Else, Infinite Impulse Response 0s (IIR)
  • 3. 6.1.1 - LTI System Transfer Function If the O/p of the system depends only on the present & past i/p samples but not on previous outputs i.e., bk=0’s outputs, i e 0s Finite Impulse Response (FIR) system , Finite Impulse Response (FIR) system H (z ) = ∑ a k z − k N k =0 h(n) = 0, n < 0, h(n) = 0, n >N, FIR system is an all zero system and are always stable If bk≠0’s, the system is called Infinite Impulse Response (IIR) system IIR filter has poles h( n) ), -∞ ≤ n ≤ ∞
  • 4. 6.1.2 - Properties of LTI Systems Using the Z- Transform Causal Systems : ROC extends outward from the outermost pole. Im R Re Stable Systems (H(z) is BIBO): ROC includes the unit circle. Im A stable system requires that its Fourier transform is uniformly convergent. 1 Re
  • 5. 6.2 - Z-transform and Frequency Response Estimation • The frequency response of a system (as digital filter spectrum) can be readily obtained from its z-transform. H(z) H( ) as, where σ is a transient term & it tends to zero as f at steady state, Steady‐state frequency response of  a system (DTFT). where, A(ω)≡ Amplitude (Magnitude) Response , B(ω) ≡ Angle (Phase) Response Steady‐state
  • 6. 6.2 - Frequency Response Estimation – cont. • Phase Delay The amount of time delay, each frequency component of the signal suffers in delay going through the system. • Group Delay The average time delay the composite signal suffers at each frequency.
  • 7. 6.3 - Inverse Z-Transform where DTFT IDTFT (A contour integral) where, for a fixed r,
  • 8. 6.3 - The Inverse Z-Transform – cont. • There is an inversion integral for the z transform, 1 x[n ] = X(z)z n−1dz j2π ∫ C but doing it requires integration in the complex plane and it is rarely used in engineering practice. • There are two other common methods, Power series method (long division method) Partial-Fraction Expansion p
  • 9. 6.3.1 - Power Series (Long Division) Method Suppose it is desired to find the inverse z transform of z2 z3 − H(z ) = 2 15 2 17 1 z − z + z− 3 12 36 18 Synthetically dividing the numerator by the denominator yields the infinite series d i t i ld th i fi it i 3 −1 67 −2 1+ z + z +L 4 144 This will always work but the answer is not in closed form (Disadvantage).
  • 10. 6.3.2 - Partial-Fraction Expansion •Put H(z-1) in a fractional form with the degree of numerator less than degree of denominator. •Put the denominator in the form of simple poles. • A l partial fraction expansion. Apply i lf i i • Apply inverse z transform for those simple fractions. Note If N: order of numerator, & M: order of denominator. then, If N=M  Divide If 1N<M  If 1N<M Make direct P.F. Make direct P F If N>M  Make long division then P.F.
  • 11. Example 1: find, a) Transfer Function b) Impulse Response -1 -1/3 7/3 *3 3 3 3 3
  • 12. Example 2: Consider the discrete system, a) ) Determine the poles & zeros. D h l b) Plot (locate) them on the z-plane. c) Discuss the stability. d) Find the impulse response. e) Find the first 4 samples of h(n) Solution: a) zeros when N(z)=0 b) z1=2 z2= - 0.5 poles when D(z)=0 xo x o 0.3 2 p1=0.3 p2= - 0.6 ‐ 0.6 ‐ 0.5 c) Since all poles lies inside the unit circle, therefore the system is stable.
  • 13. Example 2 – cont. d) As discussed before, use partial fraction expansion and the table of transformation to get the inverse z-transform c) Divide N(z) by D(z) using long division, ) () y () g g , 1 1 2 3 ‐ 0.24 ‐ 0.28 ‐ 1.8
  • 14. Example 3: Consider the system described by the following difference equation, Find, a) The transfer function. b) Th steady state frequency response. The t d t t f c) The O/p of the system when a sine wave of frequency 50 Hz & amplitude of 10 is applied at its input, the sampling frequency is 1 KHz. Solution: a)
  • 16. Example 3– cont. c) x(n) = A sin(ω0 nT + θ ) 1 = 10 sin((2π .50.n. ) + θ ) = 10 sin(0.1πn) 1000 Since the I/p is sinusoidal, the O/p should be sinusoidal, y (n) = Ay sin(0.1πn + θ y ) where, A = A A(ω ) y x 0 θ y = θ x + θ (ω0 ) 1 Ay = 10 × 1 − (0.5 cos(ω0T )) 2 + (0.5 sin(ω0T )) 2 10 = = 18.3 1 − (0.5 cos(0.1π )) 2 + (0.5 sin(0.1π )) 2 ⎛ 0.5 sin(0.1π ) ⎞ θ y = θ x − tan ⎜ −1 ⎟ = 1780 24′ ⎜ 1 − 0.5 cos(0.1π ) ⎟ ⎝ ⎠
  • 17. 6.4 Relationships between System Representations p Express H(z) in 1/z cross H(z) Take inverse z- multiply and transform take inverse Take z-transform Take solve for Y/X z-transform Difference h(n) Equation Substitute z=ejwT Take inverse DTFT Take DTFT solve H(ejwT) Take Fourier for Y/X transform