Xử lý tín hiệu số Z - Transform
Causal signals are characterized by ROCs that are outside
the maximum pole circle.
• Anticausal signals have ROCs that are inside the minimum
pole circle.
• Mixed signals have ROCs that are the annular region
between two circles—with the poles that lie inside the inner
circle contributing causally and the poles that lie outside the
outer circle contributing anticausally.
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Xử lý tín hiệu số
Z - transform
Ngô Quốc Cường
Ngô Quốc Cường
ngoquoccuong175@gmail.com
sites.google.com/a/hcmute.edu.vn/ngoquoccuong
Z - transform
• Z- transform
• Properties of Z-transform
• Inversion of Z- transform
• Analysis of LTI systems in Z domain
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4.1. Z - transform
• Given a discrete-time signal x(n), its z-transform is defined as
the following series:
where z is a complex variable.
• Writing explicitly a few of the terms:
• Z-transform is an infinite power series, it exists only for those
values of z for this series converges.
• The region of convergence (ROC) of X(z) is the set of all
values of z for which X(z) attains a finite value.
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4.1. Z - transform
• Example: Determines the z-transform of the following finite
duration signals
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4.1. Z - transform
• Solution
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4.1. Z - transform
• Example
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4.1. Z - transform
Recall that
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4.1. Z - transform
• Example
• Solution
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4.1. Z - transform
• Example
• We have (l = -n),
• Using the formula (when A<1)
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4.1. Z - transform
• We have identical closed-form expressions for the z
transform
• A closed-form expressions for the z transform does not
uniquely specify the signal in time domain.
• The ambiguity can be resolved if the ROC is specified.
• Z – transform = closed-form expressions + ROC
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4.1. Z - transform
• Example
• Solution
– The first power series converges if |z| > |a|
– The second power series converges if |z| < |b|
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• Case 1
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• Case 2
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• Characteristics families of signals with their corresponding
ROC
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4.1. Z - transform
• The z-transform of the impulse response h(n) is called the
transfer function of a digital filter:
• Determine the transfer function H(z) of the two causal filters
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4.2. Properties of Z-transform
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• Example
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• Example
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Exercise
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4.2. Properties of Z-transform
• The ROC of z-k X(z) is the same as that of X(z) except for z=0
if k>0 and z=∞ if k<0.
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• Solution
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4.2. Properties of Z-transform
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• Example
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4.2. Properties of Z-transform
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• Example
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4.2. Properties of Z-transform
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4.2. Properties of Z-transform
• Example
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4.2. Properties of Z-transform
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4.2. Properties of Z-transform
• Example
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4.2. Properties of Z-transform
• Convolution in Z domain
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4.3. RATIONAL Z-TRANSFORM
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4.3.1. Poles and Zeros
• An important family of z-transforms are those for which X(z)
is a rational function.
• Poles and Zeros
– Zeros: value of z for which X(z) = 0;
– Poles: value of z for which X(z) = ∞
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4.3.1. Poles and Zeros
• Example
• Solution
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4.3.2. Causality and Stability
• A causal signal of the form
will have z-transform
• the common ROC of all the terms will be
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4.3.2. Causality and Stability
• if the signal is completely anticausal
• the ROC is in this case
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4.3.2. Causality and Stability
• Causal signals are characterized by ROCs that are outside
the maximum pole circle.
• Anticausal signals have ROCs that are inside the minimum
pole circle.
• Mixed signals have ROCs that are the annular region
between two circles—with the poles that lie inside the inner
circle contributing causally and the poles that lie outside the
outer circle contributing anticausally.
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4.3.2. Causality and Stability
• Stability can also be characterized in the z-domain in terms of
the choice of the ROC.
• A necessary and sufficient condition for the stability of a
signal x(n) is that the ROC of the corresponding z-transform
contain the unit circle.
• A signal or system to be simultaneously stable and causal, it
is necessary that all its poles lie strictly inside the unit circle in
the z-plane.
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4.3.2. Causality and Stability
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4.3.3. System function of LTI
• System function
• From a linear constant coefficient equation
• We have,
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4.3.3. System function of LTI
• Or equivalently
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4.3.3. System function of LTI
• Example
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4.3.3. System function of LTI
• Solution
• The unit sample response
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4.4. Inverse Z- transform
• By contour integration.
• By power series expansion.
• By partial fraction expansion.
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• The partial fraction expansion method can be applied to z-
transforms that are ratios of two polynomials
• The partial fraction expansion of X(z) is given by
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• Example
• The two coefficients are obtained as follows:
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• If the degree of the numerator polynomial N(z) is exactly
equal to the degree M of the denominator D(z), then the PF
expansion must be modified
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• Example
• Compute all possible inverse z-transforms of
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• Solution
• Where
• |z| > 0.5:
• |z|<0.5:
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• Example
• Determine all inverse z-transforms of
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• Solution
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• there are only two ROCs I and II:
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MORE ABOUT INVERSE Z-TRANSFORM
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• Distinct poles
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• Multiple order poles
• Solution
• In such a case, the partial fraction expansion is:
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Exercise
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• a)
• b)
• c)
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- dsp_lec4_9055.pdf