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Analysis of Linear Time Invariable
              Systems
Linear Time Invariant (LTI) Systems
• Linearity – Linear system is a system that
  possesses the property of superposition.

• Time Invariance – A system is time invariant if
  the behavior and characteristics of the system
  are fixed over time.
Discrete – Time LTI systems :
   The Convolution Sum
System T{.}



System T{.}
Lti and z transform
Lti and z transform
Continuous– Time LTI systems :
        The Convolution Integral
• A similar approach can be drawn for
  continuous time LTI systems and following
  results can be derived.


      y(t) =   ∫   x(T)h(t-T)dT
Or,
      y(t) = x(t) h(t)
Properties of LTI systems :
Commutative
      x[n] h[n] = h[n] x[n]
Distributive
      x[n] (h1[n]+h2[n]) = x[n] h1[n] + x[n] h2[n]
Associative
      x[n] (h1[n] h2[n]) = (x[n] h1[n]) h2[n]
Stability for LTI Systems :
The output should be bounded for stability
Causality for LTI Systems
• A system is casual if the output at any time
  depends only on the values of the input at the
  present time and in the past.
• Therefore, for LTI systems, y[n] must not
  depend upon x[k] for k > n.
• Hence,
        h[n] = 0      for n < 0
Z - Transform

•   Introduction
•   Definition
•   Region of Convergence and Z Plane
•   Pole and Zero
•   Example
•   Properties
Introduction
• Since Fourier Transform has its limitations, a
  counterpart of Laplace transform (Continuous
  time) was needed for Discrete time systems.

• To perform transform analysis of unstable
  systems and to develop additional insight and
  tools for LTI systems anlysis.
Mathematical Representation
Mathematical Representation
Z Transform and
    Discrete time Fourier Transform
                                     Z = ejω
• Replace Z = rejω
                                     ω
   where r = magnitude
   ω = angle of Z
The z- transform reduces to the Fourier
transform when the magnitude of the transform
variable z is unity.
• The basic idea is to represent and analyze the
  whole system about a unit circle in Z Plane.
Region of Convergence
• Z transform of a sequence has associated with
  it a range of values of z for which X(z)
  converges. This range of values is referred to
  as the region of convergence.

• A stable system requires the ROC of z-
  transform to include the unit circle.
Pole and Zero
• When X(z) is an rational function, then
1.The roots of the numerator polynomial are
  referred to as the zeros of X(z).
2.The roots of the denominator polynomial are
  referred to as the poles of X(z).
• No poles of X(z) can occur within the region of
  convergence since the z-transform does not
  converge at a pole.
• The region of convergence is bounded by
  poles.
Example
Properties of Z transform:
Properties :
Analysis of LTI Systems using
        Z- Transform
Analysis of LTI Systems using
              Z- Transform
• From the convolution property
   Y(z) = H(z) X(z)
Where
      Y(z)= z-transform of system output.
      H(z)= z-transform of impulse response.
      X(z) = z-transform of system input .
Stability and Causality
• Causality
  – A discrete time LTI system is causal if and only if
    the ROC of its system function is the exterior of
    the circle, including infinity.


• Stability
  – The LTI system is stable if and only if the ROC of
    the system function H(z) includes the unit circle,
    |Z| = 1
Stability and Causality for LTI system
    with Rational system Function
• Causality
  – The ROC is the exterior of the outermost pole.
  – With H(z) expressed as a ratio of polynomials in z,
    the order of numerator cannot be greater than
    the order of denominator.
• Stability
  – If it is a causal system, it will be stable if and only if
    all the poles of H(z) lie inside the unit circle – i.e.
    they must all have magnitude smaller than 1.
  – It is possible for a system to be stable but not
    casual.
THANK YOU

- Pranvendra Champawat
- 08010824
- p.champawat@iitg.ernet.in

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Lti and z transform

  • 1. Analysis of Linear Time Invariable Systems
  • 2. Linear Time Invariant (LTI) Systems • Linearity – Linear system is a system that possesses the property of superposition. • Time Invariance – A system is time invariant if the behavior and characteristics of the system are fixed over time.
  • 3. Discrete – Time LTI systems : The Convolution Sum
  • 7. Continuous– Time LTI systems : The Convolution Integral • A similar approach can be drawn for continuous time LTI systems and following results can be derived. y(t) = ∫ x(T)h(t-T)dT Or, y(t) = x(t) h(t)
  • 8. Properties of LTI systems : Commutative x[n] h[n] = h[n] x[n] Distributive x[n] (h1[n]+h2[n]) = x[n] h1[n] + x[n] h2[n] Associative x[n] (h1[n] h2[n]) = (x[n] h1[n]) h2[n]
  • 9. Stability for LTI Systems :
  • 10. The output should be bounded for stability
  • 11. Causality for LTI Systems • A system is casual if the output at any time depends only on the values of the input at the present time and in the past. • Therefore, for LTI systems, y[n] must not depend upon x[k] for k > n. • Hence, h[n] = 0 for n < 0
  • 12. Z - Transform • Introduction • Definition • Region of Convergence and Z Plane • Pole and Zero • Example • Properties
  • 13. Introduction • Since Fourier Transform has its limitations, a counterpart of Laplace transform (Continuous time) was needed for Discrete time systems. • To perform transform analysis of unstable systems and to develop additional insight and tools for LTI systems anlysis.
  • 16. Z Transform and Discrete time Fourier Transform Z = ejω • Replace Z = rejω ω where r = magnitude ω = angle of Z The z- transform reduces to the Fourier transform when the magnitude of the transform variable z is unity. • The basic idea is to represent and analyze the whole system about a unit circle in Z Plane.
  • 17. Region of Convergence • Z transform of a sequence has associated with it a range of values of z for which X(z) converges. This range of values is referred to as the region of convergence. • A stable system requires the ROC of z- transform to include the unit circle.
  • 18. Pole and Zero • When X(z) is an rational function, then 1.The roots of the numerator polynomial are referred to as the zeros of X(z). 2.The roots of the denominator polynomial are referred to as the poles of X(z). • No poles of X(z) can occur within the region of convergence since the z-transform does not converge at a pole. • The region of convergence is bounded by poles.
  • 20. Properties of Z transform:
  • 22. Analysis of LTI Systems using Z- Transform
  • 23. Analysis of LTI Systems using Z- Transform • From the convolution property Y(z) = H(z) X(z) Where Y(z)= z-transform of system output. H(z)= z-transform of impulse response. X(z) = z-transform of system input .
  • 24. Stability and Causality • Causality – A discrete time LTI system is causal if and only if the ROC of its system function is the exterior of the circle, including infinity. • Stability – The LTI system is stable if and only if the ROC of the system function H(z) includes the unit circle, |Z| = 1
  • 25. Stability and Causality for LTI system with Rational system Function • Causality – The ROC is the exterior of the outermost pole. – With H(z) expressed as a ratio of polynomials in z, the order of numerator cannot be greater than the order of denominator. • Stability – If it is a causal system, it will be stable if and only if all the poles of H(z) lie inside the unit circle – i.e. they must all have magnitude smaller than 1. – It is possible for a system to be stable but not casual.
  • 26. THANK YOU - Pranvendra Champawat - 08010824 - p.champawat@iitg.ernet.in