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Advances and Applications in Mathematical Sciences
Volume 21, Issue 2, December 2021, Pages 1029-1036
© 2021 Mili Publications, India
BILINEAR TRANSFORMATION
A. SARANYA, K. CHANDRAN, A. KIRUTHIKA and B. A. BEGAM
Assistant Professor
Department of Mathematics
Dhanalakshmi Srinivasan College of Arts
and Science for Women (Autonomous)
Perambalur, India
E-mail: kasaranya92@gmail.com
r.j.malini@gmail.com
Abstract
A formula is derived and demonstrated that is capable of directly generating digital filter
coefficient from an Analog filter prototype using the bilinear transformation. This formula
obviates the need for any algebraic manipulation of the Analog prototype filter and ideal for use
in embedded systems that must be take in any general Analog filter specification and
dynamically generate digital filter coefficient directly usable in difference equations.
Introduction
The bilinear transformation is also known as Tustin’s method is used in
digital signal processing and discrete-time control theory to transform
continuous-time system representations to discrete-time and vice-versa.
A function f : C C can be thought of as a transformation from one
complex to another complex plane. Hence the nature of complex function can
be described the manner which it maps regions and curves from one complex
to another complex plane. In this chapter we shall discuss bilinear
transformation and see how various regions are transformed by the
transformations.
Definition. A Bilinear transformation is defined as
2020 Mathematics Subject Classification: 15A04.
Keywords: Bilinear transformation, Elementary transformation, Translation.
Received November 2, 2021; Accepted November 15, 2021
1030 A. SARANYA, K. CHANDRAN, A. KIRUTHIKA and B. A. BEGAM
Z a bz
c dz
Where a, b, c, d are constants (complex in general) and z is an
independent complex variables being mapped into dependent complex
variable Z as illustrated.
a b
Definition 1.1. Let a, b, c, d €C det ad bc 0. We define a
c d
bilinear transformation or a mobius transformation T : C C as:
For c 0
az b d
Tz , z C
cz d c
a
Tz , z
c
d
Tz , z ,
c
and for c 0
az b
Tz , z C
d
, z .
In general we will write a bilinear transformation T : C C as
az b
w Tz cz d , ad bc 0.
Without any ambiguity.
Example.
2z 3i iz 6
T Z , S Z , T Z 2z 3, T Z 2z,
iz 5 3z 1 2
3
S Z etc.,
1 z
Definition 1.2. (Elementary Bilinear Transformation.)
Advances and Applications in Mathematical Sciences, Volume 21, Issue 2, December 2021
BILINEAR TRANSFORMATION 10
31
1. Translation. We define a translation as where a is a
T z z a,
finite complex number, i.e. a € C. since 1z a and1. 1-a. 0 1 0,
Tz 0z 1
so T is bilinear transformation.
2. Inversion. We define inverse 1 since 0z 1 and
Tz z Tz 1z 0
00-11 -1 0, so T is a bilinear transformation.
3. Rotation. We define a rotation as i Since
T z e z, R 0 .
eiz 0 i
Tz 0z 1 and e 0, so T is bilinear transformation.
4. Magnification. We define a magnification Since
T z rz, r€R .
rz 0 and r 1 0 0 r 0, so T is bilinear transformation.
Tz 0z 1
Theorem 1.1. Every bilinear transformation is a composition of
elementary bilinear transformation, i.e. composition of translation, inversion
and dilation (one or two of them may be missing).
Proof. Let us consider a bilinear transformation T : C C defined as
az b where £C and
adbc 0
T Z cz d a, b, c, d
Case. Ic 0
az b
Hence ad 0, i.e. a 0 d and Tz d
a z b
d d
b where a and a is a dilation.
T1 z d T1z d z d 0T1
b
where translation
T2z z a
T2T1z , d
Hence T T2T1.
Case II. c 0
Advances and Applications in Mathematical Sciences, Volume 21, Issue 2, December 2021
1032 A. SARANYA, K. CHANDRAN, A. KIRUTHIKA and B. A. BEGAM
Now az d a a
Tz cz d c c
bc ad
bc ad 1 a here
c2 d c c2 0
z c
bc ad 1 a d
where translation
T1z z a
2
T1z c c
c
bc ad a where 1 is the inversion
T2T1z
T2z
2 c z
c
a where bc ad is dilation
T3 T2 T1 z c T3z c2 z
where a is translation.
T4z z
T4 T3 T2 T1z , c
Hence T T4T3T2T1. Hence the proof.
Definition. Let X be a nonempty set, and f : X X, a €X is said to be
fixed point of f if
f a 0.
Example. 1. If f : R R be the mapping defined as 2 0 and 1
fx x ,
are fixed points of f.
2. If f : R R be the mapping defined as 3 0 and ± 1 are fixed
fx x ,
points off.
3. If f : R R be the mapping defined as 0 is only fixed
f x sin x ,
points of f.
Note: for f : X X, the fixed points can be find outs by solving the
equation on X.
f x x
Example. Find all fixed points of the bilinear transformation
3z 2
Tz z 5
Solution. Here 3 is not fixed point of T.
T 1 3 ,
Advances and Applications in Mathematical Sciences, Volume 21, Issue 2, December 2021
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