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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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