Elementary Real Analysis, 2Nd Edition (2008) Section 7.2

Total Page:16

File Type:pdf, Size:1020Kb

Elementary Real Analysis, 2Nd Edition (2008) Section 7.2 ClassicalRealAnalysis.com Chapter 7 DIFFERENTIATION 7.1 Introduction Calculus courses succeed in conveying an idea of what a derivative is, and the students develop many technical skills in computations of derivatives or applications of them. We shall return to the subject of derivatives but with a different objective. Now we wish to see a little deeper and to understand the basis on which that theory develops. Much of this chapter will appear to be a review of the subject of derivatives with more attention paid to the details now and less to the applications. Some of the more advanced material will be, however, completely new. We start at the beginning, at the rudiments of the theory of derivatives. 7.2 The Derivative Let f be a function defined on an interval I and let x0 and x be points of I. Consider the difference quotient determined by the points x0 and x: f(x) f(x ) − 0 , (1) x x − 0 representing the average rate of change of f on the interval with endpoints at x and x0. 396 Thomson*Bruckner*Bruckner Elementary Real Analysis, 2nd Edition (2008) Section 7.2. The Derivative ClassicalRealAnalysis.com 397 f f(x) f(x0) x0 x Figure 7.1. The chord determined by (x, f(x)) and (x0, f(x0)). In Figure 7.1 this difference quotient represents the slope of the chord (or secant line) determined by the points (x, f(x)) and (x0, f(x0)). This same picture allows a physical interpretation. If f(x) represents the distance a point moving on a straight line has moved from some fixed point in time x, then f(x) f(x ) − 0 represents the (net) distance it has moved in the time interval [x0, x], and the difference quotient (1) represents the average velocity in that time interval. Suppose now that we fix x0, and allow x to approach x0. We learn in elementary calculus that if f(x) f(x ) lim − 0 x x0 x x → − 0 exists, then the limit represents the slope of the tangent line to the graph of the function f at the point (x0, f(x0)). In the setting of motion, the limit represents instantaneous velocity at time x0. The derivative owes its origins to these two interpretations in geometry and in the physics of motion, but now completely transcends them; the derivative finds applications in nearly every part of mathematics and the sciences. We shall study the structure of derivatives, but with less concern for computations and applications than we would have seen in our calculus courses. Now we wish to understand the notion and see why it has the properties used in the many computations and applications of the calculus. Thomson*Bruckner*Bruckner Elementary Real Analysis, 2nd Edition (2008) 398 ClassicalRealAnalysis.com Differentiation Chapter 7 7.2.1 Definition of the Derivative We begin with a familiar definition. Definition 7.1: Let f be defined on an interval I and let x I. The derivative of f at x , denoted by 0 ∈ 0 f ′(x0), is defined as f(x) f(x0) f ′(x0) = lim − , (2) x x0 x x → − 0 provided either that this limit exists or is infinite. If f ′(x0) is finite we say that f is differentiable at x0. If f is differentiable at every point of a set E I, we say that f is differentiable on E. When E is all of I, we simply say that f is a differentiable function.⊂ Note. We have allowed infinite derivatives and they do play a role in many studies, but differentiable always refers to a finite derivative. Normally the phrase “a derivative exists” also means that that derivative is finite. Example 7.2: Let f(x) = x2 on R and let x R. If x R, x = x , then 0 ∈ ∈ 6 0 f(x) f(x ) x2 x2 (x x )(x + x ) − 0 = − 0 = − 0 0 . x x x x (x x ) − 0 − 0 − 0 Since x = x , the last expression equals x + x , so 6 0 0 f(x) f(x0) lim − = lim (x + x0) = 2x0, x x0 x x x x0 → − 0 → 2 establishing the formula, f ′(x0) = 2x0 for the function f(x) = x . ◭ Let us take a moment to clarify the definition when the interval I contains one or both of its endpoints. Suppose I = [a, b]. For x0 = a (or x0 = b), the limit in (2) is just a one-sided, or unilateral, limit. The function f is defined only on [a, b] so we cannot consider points outside of that interval. Thomson*Bruckner*Bruckner Elementary Real Analysis, 2nd Edition (2008) Section 7.2. The Derivative ClassicalRealAnalysis.com 399 This brings us to another point. It can happen that a function that is not differentiable at a point x0 does satisfy the requirement of (2) from one side of x . This means that the limit in (2) exists as x x 0 → 0 from that side. We present a formal definition. Definition 7.3: Let f be defined on an interval I and let x I. The right-hand derivative of f at x , 0 ∈ 0 denoted by f+′ (x0) is the limit f(x) f(x0) f+′ (x0) = lim − , x x0+ x x → − 0 provided that one-sided limit exists or is infinite. Similarly, the left-hand derivative of f at x0, f ′ (x0), is the limit − f(x) f(x0) f ′ (x0) = lim − . − x x0 x x → − − 0 Observe that, if x0 is an interior point of I, then f ′(x0) exists if and only if f+′ (x0) = f ′ (x0). (See Exercise 7.2.8) − Example 7.4: Let f(x) = x on R. Let us consider the differentiability of f at x0 = 0. The difference quotient (1) becomes | | f(x) f(0) x 1, if x > 0 − = | | = x 0 x 1, if x < 0. − − Thus x f+′ (0) = lim | | = 1 x x0+ x → while x f ′ (0) = lim | | = 1. x x0 x − → − − The function has different right-hand and left-hand derivatives at x0 = 0 so is not differentiable at x0 = 0. ◭ Thomson*Bruckner*Bruckner Elementary Real Analysis, 2nd Edition (2008) 400 ClassicalRealAnalysis.com Differentiation Chapter 7 Figure 7.2. A function trapped between x2 and x2. − Example 7.5: (A “trapping principle”) Let f be any function defined in a neighborhood I of zero. Suppose f satisfies the inequality f(x) x2 for all x I. Thus, the graph of f is “trapped” between the parabolas y = x2 and y = x2. In| particular,| ≤ ∈ − f(0) = 0. The difference quotient computed for x0 = 0 becomes f(x) f(0) f(x) − = , x 0 x − from which we calculate f(x) x2 = x x ≤ x | | so f(x ) lim lim x = 0. x 0 x ≤ x 0 | | → → Thus f(x) lim = 0. x 0 x → As a result, f ′(0) = 0. Figure 7.2 illustrates the principle. ◭ Thomson*Bruckner*Bruckner Elementary Real Analysis, 2nd Edition (2008) Section 7.2. The Derivative ClassicalRealAnalysis.com 401 Higher-Order Derivatives When a function f is differentiable on I, it is possible that its derivative f ′ is also differentiable. When this is the case, the function f ′′ = (f ′)′ is called the second derivative of the function (n+1) (n) (n) f. Inductively, we can define derivatives of all orders: f = (f )′ (provided f is differentiable). (2) (3) When n is small, it is customary to use the convenient notation f ′′ for f , f ′′′ for f etc. Notation It is useful to have other notations for the derivative of a function f. Common notations are df dy dx and dx (when the function is expressed in the form y = f(x)). Another notation that is useful is Df. These alternate notations along with slight variations are useful for various calculations. You are no doubt familiar with such uses—the convenience of writing dy dy du = dx du dx when using the chain rule, or viewing D as an operator in solving linear differential equations. Notation can be important at times. Consider, for example, how difficult it would be to perform a simple arithmetic calculation such as the multiplication (104)(90) using Roman numerals (CIV)(XC)! Exercises 7.2.1 You might be familiar with a slightly different formulation of the definition of derivative. If x0 is interior to I, then for h sufficiently small, the point x0 + h is also in I. Show that expression (2) then reduces to ′ f(x0 + h) f(x0) f (x0) = lim − . h→0 h Repeat Examples 7.2 and 7.4 using this formulation of the derivative. See Note 161 7.2.2 Let c R. Calculate the derivatives of the functions g(x) = c and k(x) = x directly from the definition of derivative.∈ 7.2.3 Check the differentiability of each of the functions below at x0 = 0. (a) f(x) = x x | | Thomson*Bruckner*Bruckner Elementary Real Analysis, 2nd Edition (2008) 402 ClassicalRealAnalysis.com Differentiation Chapter 7 (b) f(x) = x sin x−1 (f(0) = 0) (c) f(x) = x2 sin x−1 (f(0) = 0) x2, if x rational (d) f(x) = 0, if x irrational x2, if x 0 7.2.4 Let f(x) = ax, if x≥ < 0 (a) For which values of a is f differentiable at x = 0? (b) For which values of a is f continuous at x = 0? (c) When f is differentiable at x = 0, does f ′′(0) exist? 7.2.5 For what positive values of p is the function f(x) = x p differentiable at 0? | | 7.2.6 A function f has a symmetric derivative at a point if ′ f(x + h) f(x h) fs(x) = lim − − h→0 2h ′ ′ ′ exists.
Recommended publications
  • Math 35: Real Analysis Winter 2018 Chapter 2
    Math 35: Real Analysis Winter 2018 Monday 01/22/18 Lecture 8 Chapter 2 - Sequences Chapter 2.1 - Convergent sequences Aim: Give a rigorous denition of convergence for sequences. Denition 1 A sequence (of real numbers) a : N ! R; n 7! a(n) is a function from the natural numbers to the real numbers. Though it is a function it is usually denoted as a list (an)n2N or (an)n or fang (notation from the book) The numbers a1; a2; a3;::: are called the terms of the sequence. Example 2: Find the rst ve terms of the following sequences an then sketch the sequence a) in a dot-plot. n a) (−1) . n n2N b) 2n . n! n2N c) the sequence (an)n2N dened by a1 = 1; a2 = 1 and an = an−1 + an−2 for all n ≥ 3: (Fibonacci sequence) Math 35: Real Analysis Winter 2018 Monday 01/22/18 Similar as for functions from R to R we have the following denitions for sequences: Denition 3 (bounded sequences) Let (an)n be a sequence of real numbers then a) the sequence (an)n is bounded above if there is an M 2 R, such that an ≤ M for all n 2 N : In this case M is called an upper bound of (an)n. b) the sequence (an)n is bounded below if there is an m 2 R, such that m ≤ an for all n 2 N : In this case m is called a lower bound of (an)n. c) the sequence (an)n is bounded if there is an M~ 2 R, such that janj ≤ M~ for all n 2 N : In this case M~ is called a bound of (an)n.
    [Show full text]
  • Introduction to Real Analysis I
    ROWAN UNIVERSITY Department of Mathematics Syllabus Math 01.330 - Introduction to Real Analysis I CATALOG DESCRIPTION: Math 01.330 Introduction to Real Analysis I 3 s.h. (Prerequisites: Math 01.230 Calculus III and Math 03.150 Discrete Math with a grade of C- or better in both courses) This course prepares the student for more advanced courses in analysis as well as introducing rigorous mathematical thought processes. Topics included are: sets, functions, the real number system, sequences, limits, continuity and derivatives. OBJECTIVES: Students will demonstrate the ability to use rigorous mathematical thought processes in the following areas: sets, functions, sequences, limits, continuity, and derivatives. CONTENTS: 1.0 Introduction 1.1 Real numbers 1.1.1 Absolute values, triangle inequality 1.1.2 Archimedean property, rational numbers are dense 1.2 Sets and functions 1.2.1 Set relations, cartesian product 1.2.2 One-to-one, onto, and inverse functions 1.3 Cardinality 1.3.1 One-to-one correspondence 1.3.2 Countable and uncountable sets 1.4 Methods of proof 1.4.1 Direct proof 1.4.2 Contrapositive proof 1.4.3 Proof by contradiction 1.4.4 Mathematical induction 2.0 Sequences 2.1 Convergence 2.1.1 Cauchy's epsilon definition of convergence 2.1.2 Uniqueness of limits 2.1.3 Divergence to infinity 2.1.4 Convergent sequences are bounded 2.2 Limit theorems 2.2.1 Summation/product of sequences 2.2.2 Squeeze theorem 2.3 Cauchy sequences 2.2.3 Convergent sequences are Cauchy sequences 2.2.4 Completeness axiom 2.2.5 Bounded monotone sequences are
    [Show full text]
  • Real Analysis Mathematical Knowledge for Teaching: an Investigation
    IUMPST: The Journal. Vol 1 (Content Knowledge), February 2021 [www.k-12prep.math.ttu.edu] ISSN 2165-7874 REAL ANALYSIS MATHEMATICAL KNOWLEDGE FOR TEACHING: AN INVESTIGATION Blain Patterson Virginia Military Institute [email protected] The goal of this research was to investigate the relationship between real analysis content and high school mathematics teaching so that we can ultimately better prepare our teachers to teach high school mathematics. Specifically, I investigated the following research questions. (1) What connections between real analysis and high school mathematics content do teachers make when solving tasks? (2) What real analysis content is potentially used by mathematics teachers during the instructional process? Keywords: Teacher Content Knowledge, Real Analysis, Mathematical Understanding for Secondary Teachers (MUST) Introduction What do mathematics teachers need to know to be successful in the classroom? This question has been at the forefront of mathematics education research for several years. Clearly, high school mathematics teachers should have a deep understanding of the material they teach, such as algebra, geometry, functions, probability, and statistics (Association of Mathematics Teacher Educators, 2017). However, only having knowledge of the content being taught may lead to various pedagogical difficulties, such as primarily focusing on procedural fluency rather than conceptual understanding (Ma, 1999). The general perception by mathematicians and mathematics educators alike is that teachers should have some knowledge of mathematics beyond what they teach (Association of Mathematics Teacher Educators, 2017; Conference Board of the Mathematical Sciences, 2012, Wasserman & Stockton, 2013). The rationale being that concepts from advanced mathematics courses, such as abstract algebra and real analysis, are connected to high school mathematics content (Wasserman, Fukawa-Connelly, Villanueva, Meja-Ramos, & Weber, 2017).
    [Show full text]
  • Basic Analysis I: Introduction to Real Analysis, Volume I
    Basic Analysis I Introduction to Real Analysis, Volume I by Jiríˇ Lebl June 8, 2021 (version 5.4) 2 Typeset in LATEX. Copyright ©2009–2021 Jiríˇ Lebl This work is dual licensed under the Creative Commons Attribution-Noncommercial-Share Alike 4.0 International License and the Creative Commons Attribution-Share Alike 4.0 International License. To view a copy of these licenses, visit https://creativecommons.org/licenses/ by-nc-sa/4.0/ or https://creativecommons.org/licenses/by-sa/4.0/ or send a letter to Creative Commons PO Box 1866, Mountain View, CA 94042, USA. You can use, print, duplicate, share this book as much as you want. You can base your own notes on it and reuse parts if you keep the license the same. You can assume the license is either the CC-BY-NC-SA or CC-BY-SA, whichever is compatible with what you wish to do, your derivative works must use at least one of the licenses. Derivative works must be prominently marked as such. During the writing of this book, the author was in part supported by NSF grants DMS-0900885 and DMS-1362337. The date is the main identifier of version. The major version / edition number is raised only if there have been substantial changes. Each volume has its own version number. Edition number started at 4, that is, version 4.0, as it was not kept track of before. See https://www.jirka.org/ra/ for more information (including contact information, possible updates and errata). The LATEX source for the book is available for possible modification and customization at github: https://github.com/jirilebl/ra Contents Introduction 5 0.1 About this book ....................................5 0.2 About analysis ....................................7 0.3 Basic set theory ....................................8 1 Real Numbers 21 1.1 Basic properties ...................................
    [Show full text]
  • Math 370 - Real Analysis
    Math 370 - Real Analysis G.Pugh Jan 4 2016 1 / 28 Real Analysis 2 / 28 What is Real Analysis? I Wikipedia: Real analysis. has its beginnings in the rigorous formulation of calculus. It is a branch of mathematical analysis dealing with the set of real numbers. In particular, it deals with the analytic properties of real functions and sequences, including convergence and limits of sequences of real numbers, the calculus of the real numbers, and continuity, smoothness and related properties of real-valued functions. I mathematical analysis: the branch of pure mathematics most explicitly concerned with the notion of a limit, whether the limit of a sequence or the limit of a function. It also includes the theories of differentiation, integration and measure, infinite series, and analytic functions. 3 / 28 In other words. I In calculus, we learn how to apply tools (theorems) to solve problems (optimization, related rates, linear approximation.) I In real analysis, we very carefully prove these theorems to show that they are indeed valid. 4 / 28 Thinking back to calculus. I Most every important concept was defined in terms of limits: continuity, the derivative, the definite integral I But, the notion of the limit itself was rather vague I For example, sin x lim = 1 x!0 x means sin (x)=x gets close to 1 as x gets close to 0. 5 / 28 The key notion I The key and subtle concept that makes calculus work is that of the limit I Notion of a limit was truly a major advance in mathematics. Instead of thinking of numbers as only those quantities that could be calculated in a finite number of steps, a number could be viewed as the result of a process, a target reachable after an infinite number of steps.
    [Show full text]
  • Real Analysis a Comprehensive Course in Analysis, Part 1
    Real Analysis A Comprehensive Course in Analysis, Part 1 Barry Simon Real Analysis A Comprehensive Course in Analysis, Part 1 http://dx.doi.org/10.1090/simon/001 Real Analysis A Comprehensive Course in Analysis, Part 1 Barry Simon Providence, Rhode Island 2010 Mathematics Subject Classification. Primary 26-01, 28-01, 42-01, 46-01; Secondary 33-01, 35-01, 41-01, 52-01, 54-01, 60-01. For additional information and updates on this book, visit www.ams.org/bookpages/simon Library of Congress Cataloging-in-Publication Data Simon, Barry, 1946– Real analysis / Barry Simon. pages cm. — (A comprehensive course in analysis ; part 1) Includes bibliographical references and indexes. ISBN 978-1-4704-1099-5 (alk. paper) 1. Mathematical analysis—Textbooks. I. Title. QA300.S53 2015 515.8—dc23 2014047381 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 select pages 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. Republication, systematic copying, or multiple reproduction of any material in this publication is permitted only under license from the American Mathematical Society. Permissions to reuse portions of AMS publication content are handled by Copyright Clearance Center’s RightsLink service. For more information, please visit: http://www.ams.org/rightslink. Send requests for translation rights and licensed reprints to [email protected]. Excluded from these provisions is material for which the author holds copyright.
    [Show full text]
  • Math 431 - Real Analysis I Homework Due October 31
    Math 431 - Real Analysis I Homework due October 31 In class, we learned that a function f : S ! T between metric spaces (S; dS) and (T; dT ) is continuous if and only if the pre-image of every open set in T is open in S. In other words, f is continuous if for all open U ⊂ T , the pre-image f −1(U) ⊂ S is open in S. Question 1. Let S; T , and R be metric spaces and let f : S ! T and g : T ! R. We can define the composition function g ◦ f : S ! R by g ◦ f(s) = g(f(s)): (a) Let U ⊂ R. Show that (g ◦ f)−1(U) = f −1 g−1 (U) (b) Use (a) to show that if f and g are continuous, then the composition g ◦ f is also continuous Solution 1. (a) We will show that (g ◦ f)−1(U) = f −1 g−1 (U) by showing that (g ◦ f)−1(U) ⊂ f −1 g−1 (U) and f −1 g−1 (U) ⊂ (g ◦ f)−1(U). For the first direction, let x 2 (g ◦ f)−1(U). Then, g ◦ f(x) 2 U. Thus, g(f(x)) 2 U. Since g(f(x)) 2 U, then f(x) 2 g−1(U). Continuing we get that x 2 f −1(g−1(U). Thus, (g ◦ f)−1(U) ⊂ f −1 g−1 (U) : Conversely, assume that x 2 f −1 g−1 (U). Then, f(x) 2 g−1(U). Furthermore, g(f(x)) 2 U. Thus, g ◦ f(x) 2 U.
    [Show full text]
  • Real Analysis III (Mat312β)
    Real Analysis III (MAT312β) Department of Mathematics University of Ruhuna A.W.L. Pubudu Thilan Department of Mathematics University of Ruhuna | Real Analysis III(MAT312β) 1/37 Chapter 5 Directional Derivatives and Partial Derivatives Department of Mathematics University of Ruhuna | Real Analysis III(MAT312β) 2/37 Why do we need directional derivatives? Suppose y = f (x). Then the derivative f 0(x) is the rate at which y changes when we let x vary. Since f is a function on the real line, so the variable can only increase or decrease along that single line. In one dimension, there is only one "direction" in which x can change. Department of Mathematics University of Ruhuna | Real Analysis III(MAT312β) 3/37 Why do we need directional derivatives? Cont... Given a function of two or more variables like z = f (x; y), there are infinitely many different directions from any point in which the function can change. We know that we can represent directions as vectors, particularly unit vectors when its only the direction and not the magnitude that concerns us. Directional derivatives are literally just derivatives or rates of change of a function in a particular direction. Department of Mathematics University of Ruhuna | Real Analysis III(MAT312β) 4/37 Why do we need directional derivatives? Cont... Let P is a point in the domain of f (x; y) and vectors v1, v2, v3, and v4 represent possible directions in which we might want to know the rate of change of f (x; y). Suppose we may want to know the rate at which f (x; y) is changing along or in the direction of the vector, v3, which would be the direction along the x-axis.
    [Show full text]
  • Quasi-Mean Value Theorems for Symmetrically Differentiable Functions
    Tamsui Oxford Journal of Information and Mathematical Sciences 27(3) (2011) 279-301 Aletheia University Quasi-Mean Value Theorems for Symmetrically Differentiable Functions∗ Prasanna K. Sahooy Department of Mathematics, University of Louisville, Louisville, Kentucky 40292 USA Received September 14, 2009, Accepted October 13, 2010. Abstract In this paper, we give a survey of results related the various quasi- mean value theorems for symmetrically differentiable functions and pres- ent some new results. The symmetric derivative of a real function is discussed and it's elementary properties are pointed out. Some results leading to the quasi-Lagrange mean value theorem for the symmetrically differentiable functions are presented along with some generalizations. We also present several results concerning the quasi-Flett mean value theorem for the symmetrically differentiable functions. A new result that eliminate the boundary condition in the quasi-Flett mean theorem is also included. The quasi-Flett mean value theorem of Cauchy like is surveyed along with some related results. A new result that eliminate the boundary condition is presented related to the quasi-Flett mean value theorem of Cauchy like for the symmetrically differentiable func- tions. Further, by identifying several other new auxiliary functions, we present corresponding new quasi-mean value theorems which are variant of quasi-Lagrange mean value theorem, quasi-Flett mean value theorem, and quasi-Flett mean value theorem of Cauchy like for the symmetrically differentiable functions. Keywords and Phrases: Auxiliary function, Darboux property, Flett's mean value theorem, Lagrange mean value theorem, Lagrange mean value theorem of Cauchy like, Quasi-Flett mean value theorem, Quasi-Flett mean value theorem of Cauchy like, Quasi-Lagrange mean value theorem, Symmetric derivative.
    [Show full text]
  • Real Analysis of One Variable
    Real Analysis of One Variable MATH 425/525 Fall 2011 - Overview The field of real numbers 1 Field axioms for (R; +;:) 2 Positivity axioms for R ! induce a natural order on R a > b () a − b 2 P a2 > 0; 8a 2 R∗ In particular, 1 = 12 > 0 3 Completeness axiom ! non-empty sets bounded above (resp. below) have a supremum (resp. infimum) p This is used to define x for x > 0 And to show that R n Q is not empty 4 The triangle inequality MATH 425/525 Real Analysis of One Variable Subsets of R 1 N is the intersection of all inductive subsets of R The above is used in proofs by induction One can define functions of the form x 7! x n, x 2 R and n 2 N, as well as polynomials 2 We defined the following subsets of R: Z (integers), Q (rationals) and R n Q (irrationals) 3 We proved the Archimedean property 4 We showed that Q and R n Q are dense in R 5 We can now define the Dirichlet function 1 if x 2 f (x) = Q 0 if x 2 R n Q MATH 425/525 Real Analysis of One Variable Sequences 1 Definitions of convergence and of the limit of a converging sequence 2 Properties of limits of sequences: comparison lemma, linearity, product, and quotient properties 3 Sequences and sets Every convergent sequence is bounded Sequential density of a set Closed sets A monotone sequence converges if and only if it is bounded Every sequence has a monotone subsequence Every bounded sequence has a convergent subsequence Intervals of the form [a; b] are sequentially compact 4 A sequence of numbers is convergent if and only if it is Cauchy MATH 425/525 Real Analysis of One Variable Continuity
    [Show full text]
  • Qualitative Differentiation
    transactions of the american mathematical society Volume 280, Number 1, November 1983 QUALITATIVEDIFFERENTIATION BY MICHAEL J. EVANS AND LEE LARSON Abstract. Qualitative dérivâtes and derivatives, as well as qualitative symmetric dérivâtes and derivatives, are studied in the paper. Analogues of several results known for ordinary dérivâtes and derivatives are obtained in the qualitative setting. 1. Introduction. The notions of qualitative limits, qualitative continuity, and qualitative derivatives were introduced by S. Marcus [13-15]. The purpose of the present paper is to examine qualitative differentiation and qualitative symmetric differentiation and, in particular, to present analogues of results known to hold for ordinary differentiation, symmetric differentiation, approximate differentiation, and approximate symmetric differentiation. Loosely speaking, qualitative differentiation and qualitative symmetric differentiation may be thought of as category analogues of approximate differentiation and approximate symmetric differentiation, where the set neglected near a point in the computation of difference quotients is of first category at the point in the former setting instead of density zero at the point as in the latter. We state our definitions in §2. In §3 we examine qualitative derivatives and dérivâtes. There we show that a qualitatively differentiable function on the real line is actually differentiable everywhere and obtain what may be viewed as qualitative analogues of the Denjoy-Young-Saks theorem [18]. In §4 we consider qualitative symmetric derivatives and dérivâtes. We show that with mild continuity restrictions on the primitive, a qualitative symmetric derivative must belong to Baire class one and actually be the symmetric derivative of a closely related function except at countably many points. A monotonicity theorem and related results are given.
    [Show full text]
  • Geyser Mathematicae Cassoviensis
    GEYSER MATHEMATICAE CASSOVIENSIS Košice August 2019 GEYSER MATHEMATICAE CASSOVIENSIS Košice 2019 GEYSER MATHEMATICAE CASSOVIENSIS Erika Fecková Škrabuľáková (Eds.) Cover design by: Erika Fecková Škrabuľáková Published by: Technical University of Košice, Košice, Slovakia All rights reserved c 2019 ISBN 978 - 80 - 553 - 3327 - 4 This work was supported by the Slovak Research and Development Agency under the contract No. APVV-14-0892. This work was also supported by the Union of Slovak Mathematicians and Physicists, division Košice (JSMF), SSAKI by URIVP FBERG, SAV and ZSVTS. After completing the double blind peer reviewed process of the collection of papers Geyser Ma- thematicae Cassoviensis the acceptance rate was 80 %. Introduction to GMC Dear reader, you are opening a peer review publication dedicated to new trends in Košice’s ma- thematics - Geyser Mathematicae Cassoviensis (GMC) with contributions soundly based in research or scholarship. It seeks to cover the whole field of post-school mathematical education and/or research in all areas of mathematics. It aims to take a problem-oriented approach; to help formulate the problems of higher education, to consider alternative solutions and to test them. Lastly, it seeks to inform about the up to date research in Košice and Košice’s surround via research papers, review articles and/or short communications. The education reveals abilities but do not create them. Universities educate new generations that form the national elite. Well educated people become new workers and open-minded researchers. This points out to the fact that educational activities and problems have their important place in nowadays scientific discussions. A successful academic career is increasingly linked to a track record of publishing research which is able to reach a large audience.
    [Show full text]