Exponential and Logarithmic Functions”, Chapter 7 from the Book Advanced Algebra (Index.Html) (V
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Some Transcendental Functions with an Empty Exceptional Set 3
KYUNGPOOK Math. J. 00(0000), 000-000 Some transcendental functions with an empty exceptional set F. M. S. Lima Institute of Physics, University of Brasilia, Brasilia, DF, Brazil e-mail : [email protected] Diego Marques∗ Department of Mathematics, University de Brasilia, Brasilia, DF, Brazil e-mail : [email protected] Abstract. A transcendental function usually returns transcendental values at algebraic points. The (algebraic) exceptions form the so-called exceptional set, as for instance the unitary set {0} for the function f(z)= ez , according to the Hermite-Lindemann theorem. In this note, we give some explicit examples of transcendental entire functions whose exceptional set are empty. 1 Introduction An algebraic function is a function f(x) which satisfies P (x, f(x)) = 0 for some nonzero polynomial P (x, y) with complex coefficients. Functions that can be con- structed using only a finite number of elementary operations are examples of alge- braic functions. A function which is not algebraic is, by definition, a transcendental function — e.g., basic trigonometric functions, exponential function, their inverses, etc. If f is an entire function, namely a function which is analytic in C, to say that f is a transcendental function amounts to say that it is not a polynomial. By evaluating a transcendental function at an algebraic point of its domain, one usually finds a transcendental number, but exceptions can take place. For a given transcendental function, the set of all exceptions (i.e., all algebraic numbers of the arXiv:1004.1668v2 [math.NT] 25 Aug 2012 function domain whose image is an algebraic value) form the so-called exceptional set (denoted by Sf ). -
A Computational Approach to Solve a System of Transcendental Equations with Multi-Functions and Multi-Variables
mathematics Article A Computational Approach to Solve a System of Transcendental Equations with Multi-Functions and Multi-Variables Chukwuma Ogbonnaya 1,2,* , Chamil Abeykoon 3 , Adel Nasser 1 and Ali Turan 4 1 Department of Mechanical, Aerospace and Civil Engineering, The University of Manchester, Manchester M13 9PL, UK; [email protected] 2 Faculty of Engineering and Technology, Alex Ekwueme Federal University, Ndufu Alike Ikwo, Abakaliki PMB 1010, Nigeria 3 Aerospace Research Institute and Northwest Composites Centre, School of Materials, The University of Manchester, Manchester M13 9PL, UK; [email protected] 4 Independent Researcher, Manchester M22 4ES, Lancashire, UK; [email protected] * Correspondence: [email protected]; Tel.: +44-(0)74-3850-3799 Abstract: A system of transcendental equations (SoTE) is a set of simultaneous equations containing at least a transcendental function. Solutions involving transcendental equations are often problematic, particularly in the form of a system of equations. This challenge has limited the number of equations, with inter-related multi-functions and multi-variables, often included in the mathematical modelling of physical systems during problem formulation. Here, we presented detailed steps for using a code- based modelling approach for solving SoTEs that may be encountered in science and engineering problems. A SoTE comprising six functions, including Sine-Gordon wave functions, was used to illustrate the steps. Parametric studies were performed to visualize how a change in the variables Citation: Ogbonnaya, C.; Abeykoon, affected the superposition of the waves as the independent variable varies from x1 = 1:0.0005:100 to C.; Nasser, A.; Turan, A. -
The Matrix Calculus You Need for Deep Learning
The Matrix Calculus You Need For Deep Learning Terence Parr and Jeremy Howard July 3, 2018 (We teach in University of San Francisco's MS in Data Science program and have other nefarious projects underway. You might know Terence as the creator of the ANTLR parser generator. For more material, see Jeremy's fast.ai courses and University of San Francisco's Data Institute in- person version of the deep learning course.) HTML version (The PDF and HTML were generated from markup using bookish) Abstract This paper is an attempt to explain all the matrix calculus you need in order to understand the training of deep neural networks. We assume no math knowledge beyond what you learned in calculus 1, and provide links to help you refresh the necessary math where needed. Note that you do not need to understand this material before you start learning to train and use deep learning in practice; rather, this material is for those who are already familiar with the basics of neural networks, and wish to deepen their understanding of the underlying math. Don't worry if you get stuck at some point along the way|just go back and reread the previous section, and try writing down and working through some examples. And if you're still stuck, we're happy to answer your questions in the Theory category at forums.fast.ai. Note: There is a reference section at the end of the paper summarizing all the key matrix calculus rules and terminology discussed here. arXiv:1802.01528v3 [cs.LG] 2 Jul 2018 1 Contents 1 Introduction 3 2 Review: Scalar derivative rules4 3 Introduction to vector calculus and partial derivatives5 4 Matrix calculus 6 4.1 Generalization of the Jacobian . -
IVC Factsheet Functions Comp Inverse
Imperial Valley College Math Lab Functions: Composition and Inverse Functions FUNCTION COMPOSITION In order to perform a composition of functions, it is essential to be familiar with function notation. If you see something of the form “푓(푥) = [expression in terms of x]”, this means that whatever you see in the parentheses following f should be substituted for x in the expression. This can include numbers, variables, other expressions, and even other functions. EXAMPLE: 푓(푥) = 4푥2 − 13푥 푓(2) = 4 ∙ 22 − 13(2) 푓(−9) = 4(−9)2 − 13(−9) 푓(푎) = 4푎2 − 13푎 푓(푐3) = 4(푐3)2 − 13푐3 푓(ℎ + 5) = 4(ℎ + 5)2 − 13(ℎ + 5) Etc. A composition of functions occurs when one function is “plugged into” another function. The notation (푓 ○푔)(푥) is pronounced “푓 of 푔 of 푥”, and it literally means 푓(푔(푥)). In other words, you “plug” the 푔(푥) function into the 푓(푥) function. Similarly, (푔 ○푓)(푥) is pronounced “푔 of 푓 of 푥”, and it literally means 푔(푓(푥)). In other words, you “plug” the 푓(푥) function into the 푔(푥) function. WARNING: Be careful not to confuse (푓 ○푔)(푥) with (푓 ∙ 푔)(푥), which means 푓(푥) ∙ 푔(푥) . EXAMPLES: 푓(푥) = 4푥2 − 13푥 푔(푥) = 2푥 + 1 a. (푓 ○푔)(푥) = 푓(푔(푥)) = 4[푔(푥)]2 − 13 ∙ 푔(푥) = 4(2푥 + 1)2 − 13(2푥 + 1) = [푠푚푝푙푓푦] … = 16푥2 − 10푥 − 9 b. (푔 ○푓)(푥) = 푔(푓(푥)) = 2 ∙ 푓(푥) + 1 = 2(4푥2 − 13푥) + 1 = 8푥2 − 26푥 + 1 A function can even be “composed” with itself: c. -
Some Results on the Arithmetic Behavior of Transcendental Functions
Algebra: celebrating Paulo Ribenboim’s ninetieth birthday SOME RESULTS ON THE ARITHMETIC BEHAVIOR OF TRANSCENDENTAL FUNCTIONS Diego Marques University of Brasilia October 25, 2018 After I found the famous Ribenboim’s book (Chapter 10: What kind of p p 2 number is 2 ?): Algebra: celebrating Paulo Ribenboim’s ninetieth birthday My first transcendental steps In 2005, in an undergraduate course of Abstract Algebra, the professor (G.Gurgel) defined transcendental numbers and asked about the algebraic independence of e and π. Algebra: celebrating Paulo Ribenboim’s ninetieth birthday My first transcendental steps In 2005, in an undergraduate course of Abstract Algebra, the professor (G.Gurgel) defined transcendental numbers and asked about the algebraic independence of e and π. After I found the famous Ribenboim’s book (Chapter 10: What kind of p p 2 number is 2 ?): In 1976, Mahler wrote a book entitled "Lectures on Transcendental Numbers". In its chapter 3, he left three problems, called A,B, and C. The goal of this lecture is to talk about these problems... Algebra: celebrating Paulo Ribenboim’s ninetieth birthday Kurt Mahler Kurt Mahler (Germany, 1903-Australia, 1988) Mahler’s works focus in transcendental number theory, Diophantine approximation, Diophantine equations, etc In its chapter 3, he left three problems, called A,B, and C. The goal of this lecture is to talk about these problems... Algebra: celebrating Paulo Ribenboim’s ninetieth birthday Kurt Mahler Kurt Mahler (Germany, 1903-Australia, 1988) Mahler’s works focus in transcendental number theory, Diophantine approximation, Diophantine equations, etc In 1976, Mahler wrote a book entitled "Lectures on Transcendental Numbers". -
Original Research Article Hypergeometric Functions On
Original Research Article Hypergeometric Functions on Cumulative Distribution Function ABSTRACT Exponential functions have been extended to Hypergeometric functions. There are many functions which can be expressed in hypergeometric function by using its analytic properties. In this paper, we will apply a unified approach to the probability density function and corresponding cumulative distribution function of the noncentral chi square variate to extract and derive hypergeometric functions. Key words: Generalized hypergeometric functions; Cumulative distribution theory; chi-square Distribution on Non-centrality Parameter. I) INTRODUCTION Higher-order transcendental functions are generalized from hypergeometric functions. Hypergeometric functions are special function which represents a series whose coefficients satisfy many recursion properties. These functions are applied in different subjects and ubiquitous in mathematical physics and also in computers as Maple and Mathematica. They can also give explicit solutions to problems in economics having dynamic aspects. The purpose of this paper is to understand the importance of hypergeometric function in different fields and initiating economists to the large class of hypergeometric functions which are generalized from transcendental function. The paper is organized in following way. In Section II, the generalized hypergeometric series is defined with some of its analytical properties and special cases. In Sections 3 and 4, hypergeometric function and Kummer’s confluent hypergeometric function are discussed in detail which will be directly used in our results. In Section 5, the main result is proved where we derive the exact cumulative distribution function of the noncentral chi sqaure variate. An appendix is attached which summarizes notational abbreviations and function names. The paper is introductory in nature presenting results reduced from general formulae. -
The Logic of Recursive Equations Author(S): A
The Logic of Recursive Equations Author(s): A. J. C. Hurkens, Monica McArthur, Yiannis N. Moschovakis, Lawrence S. Moss, Glen T. Whitney Source: The Journal of Symbolic Logic, Vol. 63, No. 2 (Jun., 1998), pp. 451-478 Published by: Association for Symbolic Logic Stable URL: http://www.jstor.org/stable/2586843 . Accessed: 19/09/2011 22:53 Your use of the JSTOR archive indicates your acceptance of the Terms & Conditions of Use, available at . http://www.jstor.org/page/info/about/policies/terms.jsp 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]. Association for Symbolic Logic is collaborating with JSTOR to digitize, preserve and extend access to The Journal of Symbolic Logic. http://www.jstor.org THE JOURNAL OF SYMBOLIC LOGIC Volume 63, Number 2, June 1998 THE LOGIC OF RECURSIVE EQUATIONS A. J. C. HURKENS, MONICA McARTHUR, YIANNIS N. MOSCHOVAKIS, LAWRENCE S. MOSS, AND GLEN T. WHITNEY Abstract. We study logical systems for reasoning about equations involving recursive definitions. In particular, we are interested in "propositional" fragments of the functional language of recursion FLR [18, 17], i.e., without the value passing or abstraction allowed in FLR. The 'pure," propositional fragment FLRo turns out to coincide with the iteration theories of [1]. Our main focus here concerns the sharp contrast between the simple class of valid identities and the very complex consequence relation over several natural classes of models. -
Pre-Calculus-Honors-Accelerated
PUBLIC SCHOOLS OF EDISON TOWNSHIP OFFICE OF CURRICULUM AND INSTRUCTION Pre-Calculus Honors/Accelerated/Academic Length of Course: Term Elective/Required: Required Schools: High School Eligibility: Grade 10-12 Credit Value: 5 Credits Date Approved: September 23, 2019 Pre-Calculus 2 TABLE OF CONTENTS Statement of Purpose 3 Course Objectives 4 Suggested Timeline 5 Unit 1: Functions from a Pre-Calculus Perspective 11 Unit 2: Power, Polynomial, and Rational Functions 16 Unit 3: Exponential and Logarithmic Functions 20 Unit 4: Trigonometric Function 23 Unit 5: Trigonometric Identities and Equations 28 Unit 6: Systems of Equations and Matrices 32 Unit 7: Conic Sections and Parametric Equations 34 Unit 8: Vectors 38 Unit 9: Polar Coordinates and Complex Numbers 41 Unit 10: Sequences and Series 44 Unit 11: Inferential Statistics 47 Unit 12: Limits and Derivatives 51 Pre-Calculus 3 Statement of Purpose Pre-Calculus courses combine the study of Trigonometry, Elementary Functions, Analytic Geometry, and Math Analysis topics as preparation for calculus. Topics typically include the study of complex numbers; polynomial, logarithmic, exponential, rational, right trigonometric, and circular functions, and their relations, inverses and graphs; trigonometric identities and equations; solutions of right and oblique triangles; vectors; the polar coordinate system; conic sections; Boolean algebra and symbolic logic; mathematical induction; matrix algebra; sequences and series; and limits and continuity. This course includes a review of essential skills from algebra, introduces polynomial, rational, exponential and logarithmic functions, and gives the student an in-depth study of trigonometric functions and their applications. Modern technology provides tools for supplementing the traditional focus on algebraic procedures, such as solving equations, with a more visual perspective, with graphs of equations displayed on a screen. -
Computing Transcendental Functions
Computing Transcendental Functions Iris Oved [email protected] 29 April 1999 Exponential, logarithmic, and trigonometric functions are transcendental. They are peculiar in that their values cannot be computed in terms of finite compositions of arithmetic and/or algebraic operations. So how might one go about computing such functions? There are several approaches to this problem, three of which will be outlined below. We will begin with Taylor approxima- tions, then take a look at a method involving Minimax Polynomials, and we will conclude with a brief consideration of CORDIC approximations. While the discussion will specifically cover methods for calculating the sine function, the procedures can be generalized for the calculation of other transcendental functions as well. 1 Taylor Approximations One method for computing the sine function is to find a polynomial that allows us to approximate the sine locally. A polynomial is a good approximation to the sine function near some point, x = a, if the derivatives of the polynomial at the point are equal to the derivatives of the sine curve at that point. The more derivatives the polynomial has in common with the sine function at the point, the better the approximation. Thus the higher the degree of the polynomial, the better the approximation. A polynomial that is found by this method is called a Taylor Polynomial. Suppose we are looking for the Taylor Polynomial of degree 1 approximating the sine function near x = 0. We will call the polynomial p(x) and the sine function f(x). We want to find a linear function p(x) such that p(0) = f(0) and p0(0) = f 0(0). -
Monoids: Theme and Variations (Functional Pearl)
University of Pennsylvania ScholarlyCommons Departmental Papers (CIS) Department of Computer & Information Science 7-2012 Monoids: Theme and Variations (Functional Pearl) Brent A. Yorgey University of Pennsylvania, [email protected] Follow this and additional works at: https://repository.upenn.edu/cis_papers Part of the Programming Languages and Compilers Commons, Software Engineering Commons, and the Theory and Algorithms Commons Recommended Citation Brent A. Yorgey, "Monoids: Theme and Variations (Functional Pearl)", . July 2012. This paper is posted at ScholarlyCommons. https://repository.upenn.edu/cis_papers/762 For more information, please contact [email protected]. Monoids: Theme and Variations (Functional Pearl) Abstract The monoid is a humble algebraic structure, at first glance ve en downright boring. However, there’s much more to monoids than meets the eye. Using examples taken from the diagrams vector graphics framework as a case study, I demonstrate the power and beauty of monoids for library design. The paper begins with an extremely simple model of diagrams and proceeds through a series of incremental variations, all related somehow to the central theme of monoids. Along the way, I illustrate the power of compositional semantics; why you should also pay attention to the monoid’s even humbler cousin, the semigroup; monoid homomorphisms; and monoid actions. Keywords monoid, homomorphism, monoid action, EDSL Disciplines Programming Languages and Compilers | Software Engineering | Theory and Algorithms This conference paper is available at ScholarlyCommons: https://repository.upenn.edu/cis_papers/762 Monoids: Theme and Variations (Functional Pearl) Brent A. Yorgey University of Pennsylvania [email protected] Abstract The monoid is a humble algebraic structure, at first glance even downright boring. -
Contents 3 Homomorphisms, Ideals, and Quotients
Ring Theory (part 3): Homomorphisms, Ideals, and Quotients (by Evan Dummit, 2018, v. 1.01) Contents 3 Homomorphisms, Ideals, and Quotients 1 3.1 Ring Isomorphisms and Homomorphisms . 1 3.1.1 Ring Isomorphisms . 1 3.1.2 Ring Homomorphisms . 4 3.2 Ideals and Quotient Rings . 7 3.2.1 Ideals . 8 3.2.2 Quotient Rings . 9 3.2.3 Homomorphisms and Quotient Rings . 11 3.3 Properties of Ideals . 13 3.3.1 The Isomorphism Theorems . 13 3.3.2 Generation of Ideals . 14 3.3.3 Maximal and Prime Ideals . 17 3.3.4 The Chinese Remainder Theorem . 20 3.4 Rings of Fractions . 21 3 Homomorphisms, Ideals, and Quotients In this chapter, we will examine some more intricate properties of general rings. We begin with a discussion of isomorphisms, which provide a way of identifying two rings whose structures are identical, and then examine the broader class of ring homomorphisms, which are the structure-preserving functions from one ring to another. Next, we study ideals and quotient rings, which provide the most general version of modular arithmetic in a ring, and which are fundamentally connected with ring homomorphisms. We close with a detailed study of the structure of ideals and quotients in commutative rings with 1. 3.1 Ring Isomorphisms and Homomorphisms • We begin our study with a discussion of structure-preserving maps between rings. 3.1.1 Ring Isomorphisms • We have encountered several examples of rings with very similar structures. • For example, consider the two rings R = Z=6Z and S = (Z=2Z) × (Z=3Z). -
Algebraic Values of Analytic Functions Michel Waldschmidt
Algebraic values of analytic functions Michel Waldschmidt To cite this version: Michel Waldschmidt. Algebraic values of analytic functions. International Conference on Special Functions and their Applications (ICSF02), Sep 2002, Chennai, India. pp.323-333. hal-00411427 HAL Id: hal-00411427 https://hal.archives-ouvertes.fr/hal-00411427 Submitted on 27 Aug 2009 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. Algebraic values of analytic functions Michel Waldschmidt Institut de Math´ematiques de Jussieu, Universit´eP. et M. Curie (Paris VI), Th´eorie des Nombres Case 247, 175 rue du Chevaleret 75013 PARIS [email protected] http://www.institut.math.jussieu.fr/∼miw/ Abstract Given an analytic function of one complex variable f, we investigate the arithmetic nature of the values of f at algebraic points. A typical question is whether f(α) is a transcendental number for each algebraic number α. Since there exist transcendental (t) entire functions f such that f (α) ∈ Q[α] for any t ≥ 0 and any algebraic number α, one needs to restrict the situation by adding hypotheses, either on the functions, or on the points, or else on the set of values.