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The Convolution Theorem
Module 2 : Signals in Frequency Domain Lecture 18 : The Convolution Theorem Objectives In this lecture you will learn the following We shall prove the most important theorem regarding the Fourier Transform- the Convolution Theorem We are going to learn about filters. Proof of 'the Convolution theorem for the Fourier Transform'. The Dual version of the Convolution Theorem Parseval's theorem The Convolution Theorem We shall in this lecture prove the most important theorem regarding the Fourier Transform- the Convolution Theorem. It is this theorem that links the Fourier Transform to LSI systems, and opens up a wide range of applications for the Fourier Transform. We shall inspire its importance with an application example. Modulation Modulation refers to the process of embedding an information-bearing signal into a second carrier signal. Extracting the information- bearing signal is called demodulation. Modulation allows us to transmit information signals efficiently. It also makes possible the simultaneous transmission of more than one signal with overlapping spectra over the same channel. That is why we can have so many channels being broadcast on radio at the same time which would have been impossible without modulation There are several ways in which modulation is done. One technique is amplitude modulation or AM in which the information signal is used to modulate the amplitude of the carrier signal. Another important technique is frequency modulation or FM, in which the information signal is used to vary the frequency of the carrier signal. Let us consider a very simple example of AM. Consider the signal x(t) which has the spectrum X(f) as shown : Why such a spectrum ? Because it's the simplest possible multi-valued function. -
Lecture 7: Fourier Series and Complex Power Series 1 Fourier
Math 1d Instructor: Padraic Bartlett Lecture 7: Fourier Series and Complex Power Series Week 7 Caltech 2013 1 Fourier Series 1.1 Definitions and Motivation Definition 1.1. A Fourier series is a series of functions of the form 1 C X + (a sin(nx) + b cos(nx)) ; 2 n n n=1 where C; an; bn are some collection of real numbers. The first, immediate use of Fourier series is the following theorem, which tells us that they (in a sense) can approximate far more functions than power series can: Theorem 1.2. Suppose that f(x) is a real-valued function such that • f(x) is continuous with continuous derivative, except for at most finitely many points in [−π; π]. • f(x) is periodic with period 2π: i.e. f(x) = f(x ± 2π), for any x 2 R. C P1 Then there is a Fourier series 2 + n=1 (an sin(nx) + bn cos(nx)) such that 1 C X f(x) = + (a sin(nx) + b cos(nx)) : 2 n n n=1 In other words, where power series can only converge to functions that are continu- ous and infinitely differentiable everywhere the power series is defined, Fourier series can converge to far more functions! This makes them, in practice, a quite useful concept, as in science we'll often want to study functions that aren't always continuous, or infinitely differentiable. A very specific application of Fourier series is to sound and music! Specifically, re- call/observe that a musical note with frequency f is caused by the propogation of the lon- gitudinal wave sin(2πft) through some medium. -
Topic 7 Notes 7 Taylor and Laurent Series
Topic 7 Notes Jeremy Orloff 7 Taylor and Laurent series 7.1 Introduction We originally defined an analytic function as one where the derivative, defined as a limit of ratios, existed. We went on to prove Cauchy's theorem and Cauchy's integral formula. These revealed some deep properties of analytic functions, e.g. the existence of derivatives of all orders. Our goal in this topic is to express analytic functions as infinite power series. This will lead us to Taylor series. When a complex function has an isolated singularity at a point we will replace Taylor series by Laurent series. Not surprisingly we will derive these series from Cauchy's integral formula. Although we come to power series representations after exploring other properties of analytic functions, they will be one of our main tools in understanding and computing with analytic functions. 7.2 Geometric series Having a detailed understanding of geometric series will enable us to use Cauchy's integral formula to understand power series representations of analytic functions. We start with the definition: Definition. A finite geometric series has one of the following (all equivalent) forms. 2 3 n Sn = a(1 + r + r + r + ::: + r ) = a + ar + ar2 + ar3 + ::: + arn n X = arj j=0 n X = a rj j=0 The number r is called the ratio of the geometric series because it is the ratio of consecutive terms of the series. Theorem. The sum of a finite geometric series is given by a(1 − rn+1) S = a(1 + r + r2 + r3 + ::: + rn) = : (1) n 1 − r Proof. -
Formal Power Series - Wikipedia, the Free Encyclopedia
Formal power series - Wikipedia, the free encyclopedia http://en.wikipedia.org/wiki/Formal_power_series Formal power series From Wikipedia, the free encyclopedia In mathematics, formal power series are a generalization of polynomials as formal objects, where the number of terms is allowed to be infinite; this implies giving up the possibility to substitute arbitrary values for indeterminates. This perspective contrasts with that of power series, whose variables designate numerical values, and which series therefore only have a definite value if convergence can be established. Formal power series are often used merely to represent the whole collection of their coefficients. In combinatorics, they provide representations of numerical sequences and of multisets, and for instance allow giving concise expressions for recursively defined sequences regardless of whether the recursion can be explicitly solved; this is known as the method of generating functions. Contents 1 Introduction 2 The ring of formal power series 2.1 Definition of the formal power series ring 2.1.1 Ring structure 2.1.2 Topological structure 2.1.3 Alternative topologies 2.2 Universal property 3 Operations on formal power series 3.1 Multiplying series 3.2 Power series raised to powers 3.3 Inverting series 3.4 Dividing series 3.5 Extracting coefficients 3.6 Composition of series 3.6.1 Example 3.7 Composition inverse 3.8 Formal differentiation of series 4 Properties 4.1 Algebraic properties of the formal power series ring 4.2 Topological properties of the formal power series -
Fourier Series
Academic Press Encyclopedia of Physical Science and Technology Fourier Series James S. Walker Department of Mathematics University of Wisconsin–Eau Claire Eau Claire, WI 54702–4004 Phone: 715–836–3301 Fax: 715–836–2924 e-mail: [email protected] 1 2 Encyclopedia of Physical Science and Technology I. Introduction II. Historical background III. Definition of Fourier series IV. Convergence of Fourier series V. Convergence in norm VI. Summability of Fourier series VII. Generalized Fourier series VIII. Discrete Fourier series IX. Conclusion GLOSSARY ¢¤£¦¥¨§ Bounded variation: A function has bounded variation on a closed interval ¡ ¢ if there exists a positive constant © such that, for all finite sets of points "! "! $#&% (' #*) © ¥ , the inequality is satisfied. Jordan proved that a function has bounded variation if and only if it can be expressed as the difference of two non-decreasing functions. Countably infinite set: A set is countably infinite if it can be put into one-to-one £0/"£ correspondence with the set of natural numbers ( +,£¦-.£ ). Examples: The integers and the rational numbers are countably infinite sets. "! "!;: # # 123547698 Continuous function: If , then the function is continuous at the point : . Such a point is called a continuity point for . A function which is continuous at all points is simply referred to as continuous. Lebesgue measure zero: A set < of real numbers is said to have Lebesgue measure ! $#¨CED B ¢ £¦¥ zero if, for each =?>A@ , there exists a collection of open intervals such ! ! D D J# K% $#L) ¢ £¦¥ ¥ ¢ = that <GFIH and . Examples: All finite sets, and all countably infinite sets, have Lebesgue measure zero. "! "! % # % # Odd and even functions: A function is odd if for all in its "! "! % # # domain. -
The Discovery of the Series Formula for Π by Leibniz, Gregory and Nilakantha Author(S): Ranjan Roy Source: Mathematics Magazine, Vol
The Discovery of the Series Formula for π by Leibniz, Gregory and Nilakantha Author(s): Ranjan Roy Source: Mathematics Magazine, Vol. 63, No. 5 (Dec., 1990), pp. 291-306 Published by: Mathematical Association of America Stable URL: http://www.jstor.org/stable/2690896 Accessed: 27-02-2017 22:02 UTC JSTOR is a not-for-profit service that helps scholars, researchers, and students discover, use, and build upon a wide range of content in a trusted digital archive. We use information technology and tools to increase productivity and facilitate new forms of scholarship. For more information about JSTOR, please contact [email protected]. Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at http://about.jstor.org/terms Mathematical Association of America is collaborating with JSTOR to digitize, preserve and extend access to Mathematics Magazine This content downloaded from 195.251.161.31 on Mon, 27 Feb 2017 22:02:42 UTC All use subject to http://about.jstor.org/terms ARTICLES The Discovery of the Series Formula for 7r by Leibniz, Gregory and Nilakantha RANJAN ROY Beloit College Beloit, WI 53511 1. Introduction The formula for -r mentioned in the title of this article is 4 3 57 . (1) One simple and well-known moderm proof goes as follows: x I arctan x = | 1 +2 dt x3 +5 - +2n + 1 x t2n+2 + -w3 - +(-I)rl2n+1 +(-I)l?lf dt. The last integral tends to zero if Ix < 1, for 'o t+2dt < jt dt - iX2n+3 20 as n oo. -
AN INTRODUCTION to POWER SERIES a Finite Sum of the Form A0
AN INTRODUCTION TO POWER SERIES PO-LAM YUNG A finite sum of the form n a0 + a1x + ··· + anx (where a0; : : : ; an are constants) is called a polynomial of degree n in x. One may wonder what happens if we allow an infinite number of terms instead. This leads to the study of what is called a power series, as follows. Definition 1. Given a point c 2 R, and a sequence of (real or complex) numbers a0; a1;:::; one can form a power series centered at c: 2 a0 + a1(x − c) + a2(x − c) + :::; which is also written as 1 X k ak(x − c) : k=0 For example, the following are all power series centered at 0: 1 x x2 x3 X xk (1) 1 + + + + ::: = ; 1! 2! 3! k! k=0 1 X (2) 1 + x + x2 + x3 + ::: = xk: k=0 We want to think of a power series as a function of x. Thus we are led to study carefully the convergence of such a series. Recall that an infinite series of numbers is said to converge, if the sequence given by the sum of the first N terms converges as N tends to infinity. In particular, given a real number x, the series 1 X k ak(x − c) k=0 converges, if and only if N X k lim ak(x − c) N!1 k=0 exists. A power series centered at c will surely converge at x = c (because one is just summing a bunch of zeroes then), but there is no guarantee that the series will converge for any other values x. -
The Summation of Power Series and Fourier Series
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Computational and Applied Mathematics 12&13 (1985) 447-457 447 North-Holland The summation of power series and Fourier . series I.M. LONGMAN Department of Geophysics and Planetary Sciences, Tel Aviv University, Ramat Aviv, Israel Received 27 July 1984 Abstract: The well-known correspondence of a power series with a certain Stieltjes integral is exploited for summation of the series by numerical integration. The emphasis in this paper is thus on actual summation of series. rather than mere acceleration of convergence. It is assumed that the coefficients of the series are given analytically, and then the numerator of the integrand is determined by the aid of the inverse of the two-sided Laplace transform, while the denominator is standard (and known) for all power series. Since Fourier series can be expressed in terms of power series, the method is applicable also to them. The treatment is extended to divergent series, and a fair number of numerical examples are given, in order to illustrate various techniques for the numerical evaluation of the resulting integrals. Keywork Summation of series. 1. Introduction We start by considering a power series, which it is convenient to write in the form s(x)=/.Q-~2x+&x2..., (1) for reasons which will become apparent presently. Here there is no intention to limit ourselves to alternating series since, even if the pLkare all of one sign, x may take negative and even complex values. It will be assumed in this paper that the pLk are real. -
Inverse Polynomial Expansions of Laurent Series, II
View metadata, citation and similar papers at core.ac.uk brought to you by CORE provided by Elsevier - Publisher Connector Journal of Computational and Applied Mathematics 28 (1989) 249-257 249 North-Holland Inverse polynomial expansions of Laurent series, II Arnold KNOPFMACHER Department of Computational & Applied Mathematics, University of the Witwatersrand, Johannesburg, Wits 2050, South Africa John KNOPFMACHER Department of Mathematics, University of the Witwatersrand, Johannesburg Wits ZOSO, South Africa Received 6 May 1988 Revised 23 November 1988 Abstract: An algorithm is considered, and shown to lead to various unusual and unique series expansions of formal Laurent series, as the sums of reciprocals of polynomials. The degrees of approximation by the rational functions which are the partial sums of these series are investigated. The types of series corresponding to rational functions themselves are also partially characterized. Keywords: Laurent series, polynomial, rational function, degree of approximation, series expansion. 1. Introduction Let ZP= F(( z)) denote the field of all formal Laurent series A = Cr= y c,z” in an indeterminate z, with coefficients c, all lying in a given field F. Although the main case of importance here occurs when P is the field @ of complex numbers, certain interest also attaches to other ground fields F, and almost all results below hold for arbitrary F. In certain situations below, it will be convenient to write x = z-l and also consider the ring F[x] of polynomials in x, as well as the field F(x) of rational functions in x, with coefficients in F. If c, # 0, we call v = Y(A) the order of A, and define the norm (or valuation) of A to be II A II = 2- “(A). -
Harmonic Analysis from Fourier to Wavelets
STUDENT MATHEMATICAL LIBRARY ⍀ IAS/PARK CITY MATHEMATICAL SUBSERIES Volume 63 Harmonic Analysis From Fourier to Wavelets María Cristina Pereyra Lesley A. Ward American Mathematical Society Institute for Advanced Study Harmonic Analysis From Fourier to Wavelets STUDENT MATHEMATICAL LIBRARY IAS/PARK CITY MATHEMATICAL SUBSERIES Volume 63 Harmonic Analysis From Fourier to Wavelets María Cristina Pereyra Lesley A. Ward American Mathematical Society, Providence, Rhode Island Institute for Advanced Study, Princeton, New Jersey Editorial Board of the Student Mathematical Library Gerald B. Folland Brad G. Osgood (Chair) Robin Forman John Stillwell Series Editor for the Park City Mathematics Institute John Polking 2010 Mathematics Subject Classification. Primary 42–01; Secondary 42–02, 42Axx, 42B25, 42C40. The anteater on the dedication page is by Miguel. The dragon at the back of the book is by Alexander. For additional information and updates on this book, visit www.ams.org/bookpages/stml-63 Library of Congress Cataloging-in-Publication Data Pereyra, Mar´ıa Cristina. Harmonic analysis : from Fourier to wavelets / Mar´ıa Cristina Pereyra, Lesley A. Ward. p. cm. — (Student mathematical library ; 63. IAS/Park City mathematical subseries) Includes bibliographical references and indexes. ISBN 978-0-8218-7566-7 (alk. paper) 1. Harmonic analysis—Textbooks. I. Ward, Lesley A., 1963– II. Title. QA403.P44 2012 515.2433—dc23 2012001283 Copying and reprinting. Individual readers of this publication, and nonprofit libraries acting for them, are permitted to make fair use of the material, such as to copy a chapter for use in teaching or research. Permission is granted to quote brief passages from this publication in reviews, provided the customary acknowledgment of the source is given. -
Laurent-Series-Residue-Integration.Pdf
Laurent Series RUDY DIKAIRONO AEM CHAPTER 16 Today’s Outline Laurent Series Residue Integration Method Wrap up A Sequence is a set of things (usually numbers) that are in order. (z1,z2,z3,z4…..zn) A series is a sum of a sequence of terms. (s1=z1,s2=z1+z2,s3=z1+z2+z3, … , sn) A convergent sequence is one that has a limit c. A convergent series is one whose sequence of partial sums converges. Wrap up Taylor series: or by (1), Sec 14.4 Wrap up A Maclaurin series is a Taylor series expansion of a function about zero. Wrap up Importance special Taylor’s series (Sec. 15.4) Geometric series Exponential function Wrap up Importance special Taylor’s series (Sec. 15.4) Trigonometric and hyperbolic function Wrap up Importance special Taylor’s series (Sec. 15.4) Logarithmic Lauren Series Deret Laurent adalah generalisasi dari deret Taylor. Pada deret Laurent terdapat pangkat negatif yang tidak dimiliki pada deret Taylor. Laurent’s theorem Let f(z) be analytic in a domain containing two concentric circles C1 and C2 with center Zo and the annulus between them . Then f(z) can be represented by the Laurent series Laurent’s theorem Semua koefisien dapat disajikan menjadi satu bentuk integral Example 1 Example 1: Find the Laurent series of z-5sin z with center 0. Solution. menggunakan (14) Sec.15.4 kita dapatkan. Substitution Example 2 Find the Laurent series of with center 0. Solution From (12) Sec. 15.4 with z replaced by 1/z we obtain Laurent series whose principal part is an infinite series. -
Chapter 4 the Riemann Zeta Function and L-Functions
Chapter 4 The Riemann zeta function and L-functions 4.1 Basic facts We prove some results that will be used in the proof of the Prime Number Theorem (for arithmetic progressions). The L-function of a Dirichlet character χ modulo q is defined by 1 X L(s; χ) = χ(n)n−s: n=1 P1 −s We view ζ(s) = n=1 n as the L-function of the principal character modulo 1, (1) (1) more precisely, ζ(s) = L(s; χ0 ), where χ0 (n) = 1 for all n 2 Z. We first prove that ζ(s) has an analytic continuation to fs 2 C : Re s > 0gnf1g. We use an important summation formula, due to Euler. Lemma 4.1 (Euler's summation formula). Let a; b be integers with a < b and f :[a; b] ! C a continuously differentiable function. Then b X Z b Z b f(n) = f(x)dx + f(a) + (x − [x])f 0(x)dx: n=a a a 105 Remark. This result often occurs in the more symmetric form b Z b Z b X 1 1 0 f(n) = f(x)dx + 2 (f(a) + f(b)) + (x − [x] − 2 )f (x)dx: n=a a a Proof. Let n 2 fa; a + 1; : : : ; b − 1g. Then Z n+1 Z n+1 x − [x]f 0(x)dx = (x − n)f 0(x)dx n n h in+1 Z n+1 Z n+1 = (x − n)f(x) − f(x)dx = f(n + 1) − f(x)dx: n n n By summing over n we get b Z b X Z b (x − [x])f 0(x)dx = f(n) − f(x)dx; a n=a+1 a which implies at once Lemma 4.1.