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Ch. 15 Power Series, Taylor Series
Ch. 15 Power Series, Taylor Series 서울대학교 조선해양공학과 서유택 2017.12 ※ 본 강의 자료는 이규열, 장범선, 노명일 교수님께서 만드신 자료를 바탕으로 일부 편집한 것입니다. Seoul National 1 Univ. 15.1 Sequences (수열), Series (급수), Convergence Tests (수렴판정) Sequences: Obtained by assigning to each positive integer n a number zn z . Term: zn z1, z 2, or z 1, z 2 , or briefly zn N . Real sequence (실수열): Sequence whose terms are real Convergence . Convergent sequence (수렴수열): Sequence that has a limit c limznn c or simply z c n . For every ε > 0, we can find N such that Convergent complex sequence |zn c | for all n N → all terms zn with n > N lie in the open disk of radius ε and center c. Divergent sequence (발산수열): Sequence that does not converge. Seoul National 2 Univ. 15.1 Sequences, Series, Convergence Tests Convergence . Convergent sequence: Sequence that has a limit c Ex. 1 Convergent and Divergent Sequences iin 11 Sequence i , , , , is convergent with limit 0. n 2 3 4 limznn c or simply z c n Sequence i n i , 1, i, 1, is divergent. n Sequence {zn} with zn = (1 + i ) is divergent. Seoul National 3 Univ. 15.1 Sequences, Series, Convergence Tests Theorem 1 Sequences of the Real and the Imaginary Parts . A sequence z1, z2, z3, … of complex numbers zn = xn + iyn converges to c = a + ib . if and only if the sequence of the real parts x1, x2, … converges to a . and the sequence of the imaginary parts y1, y2, … converges to b. Ex. -
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 -
Calculus 1 to 4 (2004–2006)
Calculus 1 to 4 (2004–2006) Axel Schuler¨ January 3, 2007 2 Contents 1 Real and Complex Numbers 11 Basics .......................................... 11 Notations ..................................... 11 SumsandProducts ................................ 12 MathematicalInduction. 12 BinomialCoefficients............................... 13 1.1 RealNumbers................................... 15 1.1.1 OrderedSets ............................... 15 1.1.2 Fields................................... 17 1.1.3 OrderedFields .............................. 19 1.1.4 Embedding of natural numbers into the real numbers . ....... 20 1.1.5 The completeness of Ê .......................... 21 1.1.6 TheAbsoluteValue............................ 22 1.1.7 SupremumandInfimumrevisited . 23 1.1.8 Powersofrealnumbers.. .. .. .. .. .. .. 24 1.1.9 Logarithms ................................ 26 1.2 Complexnumbers................................. 29 1.2.1 TheComplexPlaneandthePolarform . 31 1.2.2 RootsofComplexNumbers . 33 1.3 Inequalities .................................... 34 1.3.1 MonotonyofthePowerand ExponentialFunctions . ...... 34 1.3.2 TheArithmetic-Geometricmeaninequality . ...... 34 1.3.3 TheCauchy–SchwarzInequality . .. 35 1.4 AppendixA.................................... 36 2 Sequences and Series 43 2.1 ConvergentSequences .. .. .. .. .. .. .. .. 43 2.1.1 Algebraicoperationswithsequences. ..... 46 2.1.2 Somespecialsequences . .. .. .. .. .. .. 49 2.1.3 MonotonicSequences .. .. .. .. .. .. .. 50 2.1.4 Subsequences............................... 51 2.2 CauchySequences -
7. Properties of Uniformly Convergent Sequences
46 1. THE THEORY OF CONVERGENCE 7. Properties of uniformly convergent sequences Here a relation between continuity, differentiability, and Riemann integrability of the sum of a functional series or the limit of a functional sequence and uniform convergence is studied. 7.1. Uniform convergence and continuity. Theorem 7.1. (Continuity of the sum of a series) N The sum of the series un(x) of terms continuous on D R is continuous if the series converges uniformly on D. ⊂ P Let Sn(x)= u1(x)+u2(x)+ +un(x) be a sequence of partial sum. It converges to some function S···(x) because every uniformly convergent series converges pointwise. Continuity of S at a point x means (by definition) lim S(y)= S(x) y→x Fix a number ε> 0. Then one can find a number δ such that S(x) S(y) <ε whenever 0 < x y <δ | − | | − | In other words, the values S(y) can get arbitrary close to S(x) and stay arbitrary close to it for all points y = x that are sufficiently close to x. Let us show that this condition follows6 from the hypotheses. Owing to the uniform convergence of the series, given ε > 0, one can find an integer m such that ε S(x) Sn(x) sup S Sn , x D, n m | − |≤ D | − |≤ 3 ∀ ∈ ∀ ≥ Note that m is independent of x. By continuity of Sn (as a finite sum of continuous functions), for n m, one can also find a number δ > 0 such that ≥ ε Sn(x) Sn(y) < whenever 0 < x y <δ | − | 3 | − | So, given ε> 0, the integer m is found. -
Uniform Convergence and Differentiation Theorem 6.3.1
Math 341 Lecture #29 x6.3: Uniform Convergence and Differentiation We have seen that a pointwise converging sequence of continuous functions need not have a continuous limit function; we needed uniform convergence to get continuity of the limit function. What can we say about the differentiability of the limit function of a pointwise converging sequence of differentiable functions? 1+1=(2n−1) The sequence of differentiable hn(x) = x , x 2 [−1; 1], converges pointwise to the nondifferentiable h(x) = x; we will need to assume more about the pointwise converging sequence of differentiable functions to ensure that the limit function is differentiable. Theorem 6.3.1 (Differentiable Limit Theorem). Let fn ! f pointwise on the 0 closed interval [a; b], and assume that each fn is differentiable. If (fn) converges uniformly on [a; b] to a function g, then f is differentiable and f 0 = g. Proof. Let > 0 and fix c 2 [a; b]. Our goal is to show that f 0(c) exists and equals g(c). To this end, we will show the existence of δ > 0 such that for all 0 < jx − cj < δ, with x 2 [a; b], we have f(x) − f(c) − g(c) < x − c which implies that f(x) − f(c) f 0(c) = lim x!c x − c exists and is equal to g(c). The way forward is to replace (f(x) − f(c))=(x − c) − g(c) with expressions we can hopefully control: f(x) − f(c) f(x) − f(c) fn(x) − fn(c) fn(x) − fn(c) − g(c) = − + x − c x − c x − c x − c 0 0 − f (c) + f (c) − g(c) n n f(x) − f(c) fn(x) − fn(c) ≤ − x − c x − c fn(x) − fn(c) 0 0 + − f (c) + jf (c) − g(c)j: x − c n n The second and third expressions we can control respectively by the differentiability of 0 fn and the uniformly convergence of fn to g. -
G: Uniform Convergence of Fourier Series
G: Uniform Convergence of Fourier Series From previous work on the prototypical problem (and other problems) 8 < ut = Duxx 0 < x < l ; t > 0 u(0; t) = 0 = u(l; t) t > 0 (1) : u(x; 0) = f(x) 0 < x < l we developed a (formal) series solution 1 1 X X 2 2 2 nπx u(x; t) = u (x; t) = b e−n π Dt=l sin( ) ; (2) n n l n=1 n=1 2 R l nπy with bn = l 0 f(y) sin( l )dy. These are the Fourier sine coefficients for the initial data function f(x) on [0; l]. We have no real way to check that the series representation (2) is a solution to (1) because we do not know we can interchange differentiation and infinite summation. We have only assumed that up to now. In actuality, (2) makes sense as a solution to (1) if the series is uniformly convergent on [0; l] (and its derivatives also converges uniformly1). So we first discuss conditions for an infinite series to be differentiated (and integrated) term-by-term. This can be done if the infinite series and its derivatives converge uniformly. We list some results here that will establish this, but you should consult Appendix B on calculus facts, and review definitions of convergence of a series of numbers, absolute convergence of such a series, and uniform convergence of sequences and series of functions. Proofs of the following results can be found in any reasonable real analysis or advanced calculus textbook. 0.1 Differentiation and integration of infinite series Let I = [a; b] be any real interval. -
Conceptual Power Series Knowledge of STEM Majors
Paper ID #21246 Conceptual Power Series Knowledge of STEM Majors Dr. Emre Tokgoz, Quinnipiac University Emre Tokgoz is currently the Director and an Assistant Professor of Industrial Engineering at Quinnipiac University. He completed a Ph.D. in Mathematics and another Ph.D. in Industrial and Systems Engineer- ing at the University of Oklahoma. His pedagogical research interest includes technology and calculus education of STEM majors. He worked on several IRB approved pedagogical studies to observe under- graduate and graduate mathematics and engineering students’ calculus and technology knowledge since 2011. His other research interests include nonlinear optimization, financial engineering, facility alloca- tion problem, vehicle routing problem, solar energy systems, machine learning, system design, network analysis, inventory systems, and Riemannian geometry. c American Society for Engineering Education, 2018 Mathematics & Engineering Majors’ Conceptual Cognition of Power Series Emre Tokgöz [email protected] Industrial Engineering, School of Engineering, Quinnipiac University, Hamden, CT, 08518 Taylor series expansion of functions has important applications in engineering, mathematics, physics, and computer science; therefore observing responses of graduate and senior undergraduate students to Taylor series questions appears to be the initial step for understanding students’ conceptual cognitive reasoning. These observations help to determine and develop a successful teaching methodology after weaknesses of the students are investigated. Pedagogical research on understanding mathematics and conceptual knowledge of physics majors’ power series was conducted in various studies ([1-10]); however, to the best of our knowledge, Taylor series knowledge of engineering majors was not investigated prior to this study. In this work, the ability of graduate and senior undergraduate engineering and mathematics majors responding to a set of power series questions are investigated. -
Series of Functions Theorem 6.4.2
Math 341 Lecture #30 x6.4: Series of Functions Recall that we constructed the continuous nowhere differentiable function from Section 5.4 by using a series. We will develop the tools necessary to showing that this pointwise convergent series is indeed a continuous function. Definition 6.4.1. Let fn, n 2 N, and f be functions on A ⊆ R. The infinite series 1 X fn(x) = f1(x) + f2(x) + f3(x) + ··· n=1 converges pointwise on A to f(x) if the sequence of partial sums, sk(x) = f1(x) + f2(x) + ··· + fk(x) converges pointwise to f(x). The series converges uniformly on A to f if the sequence sk(x) converges uniformly on A to f(x). Uniform convergence of a series on A implies pointwise convergence of the series on A. For a pointwise or uniformly convergent series we write 1 1 X X f = fn or f(x) = fn(x): n=1 n=1 When the functions fn are continuous on A, each partial sum sk(x) is continuous on A by the Algebraic Continuity Theorem (Theorem 4.3.4). We can therefore apply the theory for uniformly convergent sequences to series. Theorem 6.4.2 (Term-by-term Continuity Theorem). Let fn be continuous functions on A ⊆ . If R 1 X fn n=1 converges uniformly to f on A, then f is continuous on A. Proof. We apply Theorem 6.2.6 to the partial sums sk = f1 + f2 + ··· + fk. When the functions fn are differentiable on a closed interval [a; b], we have that each partial sum sk is differentiable on [a; b] as well. -
1 Infinite Sequences and Series
1 Infinite Sequences and Series In experimental science and engineering, as well as in everyday life, we deal with integers, or at most rational numbers. Yet in theoretical analysis, we use real and complex numbers, as well as far more abstract mathematical constructs, fully expecting that this analysis will eventually provide useful models of natural phenomena. Hence we proceed through the con- struction of the real and complex numbers starting from the positive integers1. Understanding this construction will help the reader appreciate many basic ideas of analysis. We start with the positive integers and zero, and introduce negative integers to allow sub- traction of integers. Then we introduce rational numbers to permit division by integers. From arithmetic we proceed to analysis, which begins with the concept of convergence of infinite sequences of (rational) numbers, as defined here by the Cauchy criterion. Then we define irrational numbers as limits of convergent (Cauchy) sequences of rational numbers. In order to solve algebraic equations in general, we must introduce complex numbers and the representation of complex numbers as points in the complex plane. The fundamental theorem of algebra states that every polynomial has at least one root in the complex plane, from which it follows that every polynomial of degree n has exactly n roots in the complex plane when these roots are suitably counted. We leave the proof of this theorem until we study functions of a complex variable at length in Chapter 4. Once we understand convergence of infinite sequences, we can deal with infinite series of the form ∞ xn n=1 and the closely related infinite products of the form ∞ xn n=1 Infinite series are central to the study of solutions, both exact and approximate, to the differ- ential equations that arise in every branch of physics. -
Classical Analysis
Classical Analysis Edmund Y. M. Chiang December 3, 2009 Abstract This course assumes students to have mastered the knowledge of complex function theory in which the classical analysis is based. Either the reference book by Brown and Churchill [6] or Bak and Newman [4] can provide such a background knowledge. In the all-time classic \A Course of Modern Analysis" written by Whittaker and Watson [23] in 1902, the authors divded the content of their book into part I \The processes of analysis" and part II \The transcendental functions". The main theme of this course is to study some fundamentals of these classical transcendental functions which are used extensively in number theory, physics, engineering and other pure and applied areas. Contents 1 Separation of Variables of Helmholtz Equations 3 1.1 What is not known? . .8 2 Infinite Products 9 2.1 Definitions . .9 2.2 Cauchy criterion for infinite products . 10 2.3 Absolute and uniform convergence . 11 2.4 Associated series of logarithms . 14 2.5 Uniform convergence . 15 3 Gamma Function 20 3.1 Infinite product definition . 20 3.2 The Euler (Mascheroni) constant γ ............... 21 3.3 Weierstrass's definition . 22 3.4 A first order difference equation . 25 3.5 Integral representation definition . 25 3.6 Uniform convergence . 27 3.7 Analytic properties of Γ(z)................... 30 3.8 Tannery's theorem . 32 3.9 Integral representation . 33 3.10 The Eulerian integral of the first kind . 35 3.11 The Euler reflection formula . 37 3.12 Stirling's asymptotic formula . 40 3.13 Gauss's Multiplication Formula . -
Sequences and Series of Functions, Convergence, Power Series
6: SEQUENCES AND SERIES OF FUNCTIONS, CONVERGENCE STEVEN HEILMAN Contents 1. Review 1 2. Sequences of Functions 2 3. Uniform Convergence and Continuity 3 4. Series of Functions and the Weierstrass M-test 5 5. Uniform Convergence and Integration 6 6. Uniform Convergence and Differentiation 7 7. Uniform Approximation by Polynomials 9 8. Power Series 10 9. The Exponential and Logarithm 15 10. Trigonometric Functions 17 11. Appendix: Notation 20 1. Review Remark 1.1. From now on, unless otherwise specified, Rn refers to Euclidean space Rn n with n ≥ 1 a positive integer, and where we use the metric d`2 on R . In particular, R refers to the metric space R equipped with the metric d(x; y) = jx − yj. (j) 1 Proposition 1.2. Let (X; d) be a metric space. Let (x )j=k be a sequence of elements of X. 0 (j) 1 Let x; x be elements of X. Assume that the sequence (x )j=k converges to x with respect to (j) 1 0 0 d. Assume also that the sequence (x )j=k converges to x with respect to d. Then x = x . Proposition 1.3. Let a < b be real numbers, and let f :[a; b] ! R be a function which is both continuous and strictly monotone increasing. Then f is a bijection from [a; b] to [f(a); f(b)], and the inverse function f −1 :[f(a); f(b)] ! [a; b] is also continuous and strictly monotone increasing. Theorem 1.4 (Inverse Function Theorem). Let X; Y be subsets of R. -
Complex Analysis Mario Bonk
Complex Analysis Mario Bonk Course notes for Math 246A and 246B University of California, Los Angeles Contents Preface 6 1 Algebraic properties of complex numbers 8 2 Topological properties of C 18 3 Differentiation 26 4 Path integrals 38 5 Power series 43 6 Local Cauchy theorems 55 7 Power series representations 62 8 Zeros of holomorphic functions 68 9 The Open Mapping Theorem 74 10 Elementary functions 79 11 The Riemann sphere 86 12 M¨obiustransformations 92 13 Schwarz's Lemma 105 14 Winding numbers 113 15 Global Cauchy theorems 122 16 Isolated singularities 129 17 The Residue Theorem 142 18 Normal families 152 19 The Riemann Mapping Theorem 161 3 CONTENTS 4 20 The Cauchy transform 170 21 Runge's Approximation Theorem 179 References 187 Preface These notes cover the material of a course on complex analysis that I taught repeatedly at UCLA. In many respects I closely follow Rudin's book on \Real and Complex Analysis". Since Walter Rudin is the unsurpassed master of mathematical exposition for whom I have great admiration, I saw no point in trying to improve on his presentation of subjects that are relevant for the course. The notes give a fairly accurate account of the material covered in class. They are rather terse as oral discussions that gave further explanations or put results into perspective are mostly omitted. In addition, all pictures and diagrams are currently missing as it is much easier to produce them on the blackboard than to put them into print. 6 1 Algebraic properties of complex numbers 1.1.