5.7 Inverse Trigonometric Functions: Integration 375
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ECE3040: Table of Contents
ECE3040: Table of Contents Lecture 1: Introduction and Overview Instructor contact information Navigating the course web page What is meant by numerical methods? Example problems requiring numerical methods What is Matlab and why do we need it? Lecture 2: Matlab Basics I The Matlab environment Basic arithmetic calculations Command Window control & formatting Built-in constants & elementary functions Lecture 3: Matlab Basics II The assignment operator “=” for defining variables Creating and manipulating arrays Element-by-element array operations: The “.” Operator Vector generation with linspace function and “:” (colon) operator Graphing data and functions Lecture 4: Matlab Programming I Matlab scripts (programs) Input-output: The input and disp commands The fprintf command User-defined functions Passing functions to M-files: Anonymous functions Global variables Lecture 5: Matlab Programming II Making decisions: The if-else structure The error, return, and nargin commands Loops: for and while structures Interrupting loops: The continue and break commands Lecture 6: Programming Examples Plotting piecewise functions Computing the factorial of a number Beeping Looping vs vectorization speed: tic and toc commands Passing an “anonymous function” to Matlab function Approximation of definite integrals: Riemann sums Computing cos(푥) from its power series Stopping criteria for iterative numerical methods Computing the square root Evaluating polynomials Errors and Significant Digits Lecture 7: Polynomials Polynomials -
Elementary Functions: Towards Automatically Generated, Efficient
Elementary functions : towards automatically generated, efficient, and vectorizable implementations Hugues De Lassus Saint-Genies To cite this version: Hugues De Lassus Saint-Genies. Elementary functions : towards automatically generated, efficient, and vectorizable implementations. Other [cs.OH]. Université de Perpignan, 2018. English. NNT : 2018PERP0010. tel-01841424 HAL Id: tel-01841424 https://tel.archives-ouvertes.fr/tel-01841424 Submitted on 17 Jul 2018 HAL is a multi-disciplinary open access L’archive ouverte pluridisciplinaire HAL, est archive for the deposit and dissemination of sci- destinée au dépôt et à la diffusion de documents entific research documents, whether they are pub- scientifiques de niveau recherche, publiés ou non, lished or not. The documents may come from émanant des établissements d’enseignement et de teaching and research institutions in France or recherche français ou étrangers, des laboratoires abroad, or from public or private research centers. publics ou privés. Délivré par l’Université de Perpignan Via Domitia Préparée au sein de l’école doctorale 305 – Énergie et Environnement Et de l’unité de recherche DALI – LIRMM – CNRS UMR 5506 Spécialité: Informatique Présentée par Hugues de Lassus Saint-Geniès [email protected] Elementary functions: towards automatically generated, efficient, and vectorizable implementations Version soumise aux rapporteurs. Jury composé de : M. Florent de Dinechin Pr. INSA Lyon Rapporteur Mme Fabienne Jézéquel MC, HDR UParis 2 Rapporteur M. Marc Daumas Pr. UPVD Examinateur M. Lionel Lacassagne Pr. UParis 6 Examinateur M. Daniel Menard Pr. INSA Rennes Examinateur M. Éric Petit Ph.D. Intel Examinateur M. David Defour MC, HDR UPVD Directeur M. Guillaume Revy MC UPVD Codirecteur À la mémoire de ma grand-mère Françoise Lapergue et de Jos Perrot, marin-pêcheur bigouden. -
Package 'Mosaiccalc'
Package ‘mosaicCalc’ May 7, 2020 Type Package Title Function-Based Numerical and Symbolic Differentiation and Antidifferentiation Description Part of the Project MOSAIC (<http://mosaic-web.org/>) suite that provides utility functions for doing calculus (differentiation and integration) in R. The main differentiation and antidifferentiation operators are described using formulas and return functions rather than numerical values. Numerical values can be obtained by evaluating these functions. Version 0.5.1 Depends R (>= 3.0.0), mosaicCore Imports methods, stats, MASS, mosaic, ggformula, magrittr, rlang Suggests testthat, knitr, rmarkdown, mosaicData Author Daniel T. Kaplan <[email protected]>, Ran- dall Pruim <[email protected]>, Nicholas J. Horton <[email protected]> Maintainer Daniel Kaplan <[email protected]> VignetteBuilder knitr License GPL (>= 2) LazyLoad yes LazyData yes URL https://github.com/ProjectMOSAIC/mosaicCalc BugReports https://github.com/ProjectMOSAIC/mosaicCalc/issues RoxygenNote 7.0.2 Encoding UTF-8 NeedsCompilation no Repository CRAN Date/Publication 2020-05-07 13:00:13 UTC 1 2 D R topics documented: connector . .2 D..............................................2 findZeros . .4 fitSpline . .5 integrateODE . .5 numD............................................6 plotFun . .7 rfun .............................................7 smoother . .7 spliner . .7 Index 8 connector Create an interpolating function going through a set of points Description This is defined in the mosaic package: See connector. D Derivative and Anti-derivative operators Description Operators for computing derivatives and anti-derivatives as functions. Usage D(formula, ..., .hstep = NULL, add.h.control = FALSE) antiD(formula, ..., lower.bound = 0, force.numeric = FALSE) makeAntiDfun(.function, .wrt, from, .tol = .Machine$double.eps^0.25) numerical_integration(f, wrt, av, args, vi.from, ciName = "C", .tol) D 3 Arguments formula A formula. -
Calculus 141, Section 8.5 Symbolic Integration Notes by Tim Pilachowski
Calculus 141, section 8.5 Symbolic Integration notes by Tim Pilachowski Back in my day (mid-to-late 1970s for high school and college) we had no handheld calculators, and the only electronic computers were mainframes at universities and government facilities. After learning the integration techniques that you are now learning, we were sent to Tables of Integrals, which listed results for (often) hundreds of simple to complicated integration results. Some could be evaluated using the methods of Calculus 1 and 2, others needed more esoteric methods. It was necessary to scan the Tables to find the form that was needed. If it was there, great! If not… The UMCP Physics Department posts one from the textbook they use (current as of 2017) at www.physics.umd.edu/hep/drew/IntegralTable.pdf . A similar Table of Integrals from http://www.had2know.com/academics/table-of-integrals-antiderivative-formulas.html is appended at the end of this Lecture outline. x 1 x Example F from 8.1: Evaluate e sindxx using a Table of Integrals. Answer : e ()sin x − cos x + C ∫ 2 If you remember, we had to define I, do a series of two integrations by parts, then solve for “ I =”. From the Had2Know Table of Integrals below: Identify a = and b = , then plug those values in, and voila! Now, with the development of handheld calculators and personal computers, much more is available to us, including software that will do all the work. The text mentions Derive, Maple, Mathematica, and MATLAB, and gives examples of Mathematica commands. You’ll be using MATLAB in Math 241 and several other courses. -
Symbolic and Numerical Integration in MATLAB 1 Symbolic Integration in MATLAB
Symbolic and Numerical Integration in MATLAB 1 Symbolic Integration in MATLAB Certain functions can be symbolically integrated in MATLAB with the int command. Example 1. Find an antiderivative for the function f(x)= x2. We can do this in (at least) three different ways. The shortest is: >>int(’xˆ2’) ans = 1/3*xˆ3 Alternatively, we can define x symbolically first, and then leave off the single quotes in the int statement. >>syms x >>int(xˆ2) ans = 1/3*xˆ3 Finally, we can first define f as an inline function, and then integrate the inline function. >>syms x >>f=inline(’xˆ2’) f = Inline function: >>f(x) = xˆ2 >>int(f(x)) ans = 1/3*xˆ3 In certain calculations, it is useful to define the antiderivative as an inline function. Given that the preceding lines of code have already been typed, we can accomplish this with the following commands: >>intoff=int(f(x)) intoff = 1/3*xˆ3 >>intoff=inline(char(intoff)) intoff = Inline function: intoff(x) = 1/3*xˆ3 1 The inline function intoff(x) has now been defined as the antiderivative of f(x)= x2. The int command can also be used with limits of integration. △ Example 2. Evaluate the integral 2 x cos xdx. Z1 In this case, we will only use the first method from Example 1, though the other two methods will work as well. We have >>int(’x*cos(x)’,1,2) ans = cos(2)+2*sin(2)-cos(1)-sin(1) >>eval(ans) ans = 0.0207 Notice that since MATLAB is working symbolically here the answer it gives is in terms of the sine and cosine of 1 and 2 radians. -
What Is a Closed-Form Number? Timothy Y. Chow the American
What is a Closed-Form Number? Timothy Y. Chow The American Mathematical Monthly, Vol. 106, No. 5. (May, 1999), pp. 440-448. Stable URL: http://links.jstor.org/sici?sici=0002-9890%28199905%29106%3A5%3C440%3AWIACN%3E2.0.CO%3B2-6 The American Mathematical Monthly is currently published by Mathematical Association of America. Your use of the JSTOR archive indicates your acceptance of JSTOR's Terms and Conditions of Use, available at http://www.jstor.org/about/terms.html. JSTOR's Terms and Conditions of Use provides, in part, that unless you have obtained prior permission, you may not download an entire issue of a journal or multiple copies of articles, and you may use content in the JSTOR archive only for your personal, non-commercial use. Please contact the publisher regarding any further use of this work. Publisher contact information may be obtained at http://www.jstor.org/journals/maa.html. Each copy of any part of a JSTOR transmission must contain the same copyright notice that appears on the screen or printed page of such transmission. JSTOR is an independent not-for-profit organization dedicated to and preserving a digital archive of scholarly journals. For more information regarding JSTOR, please contact [email protected]. http://www.jstor.org Mon May 14 16:45:04 2007 What Is a Closed-Form Number? Timothy Y. Chow 1. INTRODUCTION. When I was a high-school student, I liked giving exact answers to numerical problems whenever possible. If the answer to a problem were 2/7 or n-6 or arctan 3 or el/" I would always leave it in that form instead of giving a decimal approximation. -
Integration Benchmarks for Computer Algebra Systems
The Electronic Journal of Mathematics and Technology, Volume 2, Number 3, ISSN 1933-2823 Integration on Computer Algebra Systems Kevin Charlwood e-mail: [email protected] Washburn University Topeka, KS 66621 Abstract In this article, we consider ten indefinite integrals and the ability of three computer algebra systems (CAS) to evaluate them in closed-form, appealing only to the class of real, elementary functions. Although these systems have been widely available for many years and have undergone major enhancements in new versions, it is interesting to note that there are still indefinite integrals that escape the capacity of these systems to provide antiderivatives. When this occurs, we consider what a user may do to find a solution with the aid of a CAS. 1. Introduction We will explore the use of three CAS’s in the evaluation of indefinite integrals: Maple 11, Mathematica 6.0.2 and the Texas Instruments (TI) 89 Titanium graphics calculator. We consider integrals of real elementary functions of a single real variable in the examples that follow. Students often believe that a good CAS will enable them to solve any problem when there is a known solution; these examples are useful in helping instructors show their students that this is not always the case, even in a calculus course. A CAS may provide a solution, but in a form containing special functions unfamiliar to calculus students, or too cumbersome for students to use directly, [1]. Students may ask, “Why do we need to learn integration methods when our CAS will do all the exercises in the homework?” As instructors, we want our students to come away from their mathematics experience with some capacity to make intelligent use of a CAS when needed. -
Sequences, Series and Taylor Approximation (Ma2712b, MA2730)
Sequences, Series and Taylor Approximation (MA2712b, MA2730) Level 2 Teaching Team Current curator: Simon Shaw November 20, 2015 Contents 0 Introduction, Overview 6 1 Taylor Polynomials 10 1.1 Lecture 1: Taylor Polynomials, Definition . .. 10 1.1.1 Reminder from Level 1 about Differentiable Functions . .. 11 1.1.2 Definition of Taylor Polynomials . 11 1.2 Lectures 2 and 3: Taylor Polynomials, Examples . ... 13 x 1.2.1 Example: Compute and plot Tnf for f(x) = e ............ 13 1.2.2 Example: Find the Maclaurin polynomials of f(x) = sin x ...... 14 2 1.2.3 Find the Maclaurin polynomial T11f for f(x) = sin(x ) ....... 15 1.2.4 QuestionsforChapter6: ErrorEstimates . 15 1.3 Lecture 4 and 5: Calculus of Taylor Polynomials . .. 17 1.3.1 GeneralResults............................... 17 1.4 Lecture 6: Various Applications of Taylor Polynomials . ... 22 1.4.1 RelativeExtrema .............................. 22 1.4.2 Limits .................................... 24 1.4.3 How to Calculate Complicated Taylor Polynomials? . 26 1.5 ExerciseSheet1................................... 29 1.5.1 ExerciseSheet1a .............................. 29 1.5.2 FeedbackforSheet1a ........................... 33 2 Real Sequences 40 2.1 Lecture 7: Definitions, Limit of a Sequence . ... 40 2.1.1 DefinitionofaSequence .......................... 40 2.1.2 LimitofaSequence............................. 41 2.1.3 Graphic Representations of Sequences . .. 43 2.2 Lecture 8: Algebra of Limits, Special Sequences . ..... 44 2.2.1 InfiniteLimits................................ 44 1 2.2.2 AlgebraofLimits.............................. 44 2.2.3 Some Standard Convergent Sequences . .. 46 2.3 Lecture 9: Bounded and Monotone Sequences . ..... 48 2.3.1 BoundedSequences............................. 48 2.3.2 Convergent Sequences and Closed Bounded Intervals . .... 48 2.4 Lecture10:MonotoneSequences . -
Elementary Functions and Their Inverses*
ELEMENTARYFUNCTIONS AND THEIR INVERSES* BY J. F. RITT The chief item of this paper is the determination of all elementary functions whose inverses are elementary. The elementary functions are understood here to be those which are obtained in a finite number of steps by performing algebraic operations and taking exponentials and logarithms. For instance, the function tan \cf — log,(l + Vz)] + [«*+ log arc sin*]1« is elementary. We prove that if F(z) and its inverse are both elementary, there exist n functions Vt(*)j <hiz), •', <Pniz), where each <piz) with an odd index is algebraic, and each (p(z) with an even index is either e? or log?, such that F(g) = <pn(pn-f-<Pn9i(z) each q>i(z)ii<ît) being substituted for z in ^>iiiz). That every F(z) of this type has an elementary inverse is obvious. It remains to develop a method for recognizing whether a given elementary function can be reduced to the above form for F(.z). How to test fairly simple functions will be evident from the details of our proofs. For the immediate present, we let the general question stand. The present paper is an addition to Liouville's work of almost a century ago on the classification of the elementary functions, on the possibility of effecting integrations in finite terms, and on the impossibility of solving certain differentia] equations, and certain transcendental equations, in finite terms.!" Free use is made here of the ingenious methods of Liouville. * Presented to the Society, October 25, 1924. -(•Journal de l'Ecole Polytechnique, vol. -
Multivariable Calculus with Maxima
Multivariable Calculus with Maxima G. Jay Kerns December 1, 2009 The following is a short guide to multivariable calculus with Maxima. It loosely follows the treatment of Stewart’s Calculus, Seventh Edition. Refer there for definitions, theorems, proofs, explanations, and exercises. The simple goal of this guide is to demonstrate how to use Maxima to solve problems in that vein. This was originally written for the students in my third semester Calculus class, but once it grew past twenty pages I thought it might be of interest to a wider audience. Here it is. I am releasing this as a FREE document, and other people are free to build on this to make it better. The source for this document is located at http://people.ysu.edu/~gkerns/maxima/ It was inspired by Maxima by Example by Edwin Woollett, A Maxima Guide for Calculus Students by Moses Glasner, and Tutorial on Maxima by unknown. I also received help from the Maxima mailing list archives and volunteer responses to my questions. Thanks to all of those individuals. Contents 1 Getting Maxima 4 1.1 How to Install imaxima for Microsoft Windowsr ................ 4 1.1.1 Install the software ............................ 5 1.1.2 Configure your system .......................... 5 2 Three Dimensional Geometry 6 2.1 Vectors and Linear Algebra ........................... 6 2.2 Lines, Planes, and Quadric Surfaces ....................... 8 2.3 Vector Valued Functions ............................. 14 2.4 Arc Length and Curvature ............................ 19 3 Functions of Several Variables 20 3.1 Partial Derivatives ................................ 23 3.2 Linear Approximation and Differentials ..................... 24 3.3 Chain Rule and Implicit Differentiation .................... -
Arxiv:1911.10319V2 [Math.CA] 29 Dec 2019 Roswl Egvni H Etscin.Atraiey Ecnuse Can We Alternatively, Sections
Elementary hypergeometric functions, Heun functions, and moments of MKZ operators Ana-Maria Acu1a, Ioan Rasab aLucian Blaga University of Sibiu, Department of Mathematics and Informatics, Str. Dr. I. Ratiu, No.5-7, RO-550012 Sibiu, Romania, e-mail: [email protected] bTechnical University of Cluj-Napoca, Faculty of Automation and Computer Science, Department of Mathematics, Str. Memorandumului nr. 28 Cluj-Napoca, Romania, e-mail: [email protected] Abstract We consider some hypergeometric functions and prove that they are elementary functions. Con- sequently, the second order moments of Meyer-K¨onig and Zeller type operators are elementary functions. The higher order moments of these operators are expressed in terms of elementary func- tions and polylogarithms. Other applications are concerned with the expansion of certain Heun functions in series or finite sums of elementary hypergeometric functions. Keywords: hypergeometric functions, elementary functions, Meyer-K¨onig and Zeller type operators, polylogarithms; Heun functions 2010 MSC: 33C05, 33C90, 33E30, 41A36 1. Introduction This paper is devoted to some families of elementary hypergeometric functions, with applica- tions to the moments of Meyer-K¨onig and Zeller type operators and to the expansion of certain Heun functions in series or finite sums of elementary hypergeometric functions. In [4], J.A.H. Alkemade proved that the second order moment of the Meyer-K¨onig and Zeller operators can be expressed as 2 2 x(1 − x) Mn(e2; x)= x + 2F1(1, 2; n + 2; x), x ∈ [0, 1). (1.1) arXiv:1911.10319v2 [math.CA] 29 Dec 2019 n +1 r Here er(t) := t , t ∈ [0, 1], r ≥ 0, and 2F1(a,b; c; x) denotes the hypergeometric function. -
Highlighting Wxmaxima in Calculus
mathematics Article Not Another Computer Algebra System: Highlighting wxMaxima in Calculus Natanael Karjanto 1,* and Husty Serviana Husain 2 1 Department of Mathematics, University College, Natural Science Campus, Sungkyunkwan University Suwon 16419, Korea 2 Department of Mathematics Education, Faculty of Mathematics and Natural Science Education, Indonesia University of Education, Bandung 40154, Indonesia; [email protected] * Correspondence: [email protected] Abstract: This article introduces and explains a computer algebra system (CAS) wxMaxima for Calculus teaching and learning at the tertiary level. The didactic reasoning behind this approach is the need to implement an element of technology into classrooms to enhance students’ understanding of Calculus concepts. For many mathematics educators who have been using CAS, this material is of great interest, particularly for secondary teachers and university instructors who plan to introduce an alternative CAS into their classrooms. By highlighting both the strengths and limitations of the software, we hope that it will stimulate further debate not only among mathematics educators and software users but also also among symbolic computation and software developers. Keywords: computer algebra system; wxMaxima; Calculus; symbolic computation Citation: Karjanto, N.; Husain, H.S. 1. Introduction Not Another Computer Algebra A computer algebra system (CAS) is a program that can solve mathematical problems System: Highlighting wxMaxima in by rearranging formulas and finding a formula that solves the problem, as opposed to Calculus. Mathematics 2021, 9, 1317. just outputting the numerical value of the result. Maxima is a full-featured open-source https://doi.org/10.3390/ CAS: the software can serve as a calculator, provide analytical expressions, and perform math9121317 symbolic manipulations.