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Partial Fractions Decompositions (Includes the Coverup Method)
Partial Fractions and the Coverup Method 18.031 Haynes Miller and Jeremy Orloff *Much of this note is freely borrowed from an MIT 18.01 note written by Arthur Mattuck. 1 Heaviside Cover-up Method 1.1 Introduction The cover-up method was introduced by Oliver Heaviside as a fast way to do a decomposition into partial fractions. This is an essential step in using the Laplace transform to solve differential equations, and this was more or less Heaviside's original motivation. The cover-up method can be used to make a partial fractions decomposition of a proper p(s) rational function whenever the denominator can be factored into distinct linear factors. q(s) Note: We put this section first, because the coverup method is so useful and many people have not seen it. Some of the later examples rely on the full algebraic method of undeter- mined coefficients presented in the next section. If you have never seen partial fractions you should read that section first. 1.2 Linear Factors We first show how the method works on a simple example, and then show why it works. s − 7 Example 1. Decompose into partial fractions. (s − 1)(s + 2) answer: We know the answer will have the form s − 7 A B = + : (1) (s − 1)(s + 2) s − 1 s + 2 To determine A by the cover-up method, on the left-hand side we mentally remove (or cover up with a finger) the factor s − 1 associated with A, and substitute s = 1 into what's left; this gives A: s − 7 1 − 7 = = −2 = A: (2) (s + 2) s=1 1 + 2 Similarly, B is found by covering up the factor s + 2 on the left, and substituting s = −2 into what's left. -
Z-Transform Part 2 February 23, 2017 1 / 38 the Z-Transform and Its Application to the Analysis of LTI Systems
ELC 4351: Digital Signal Processing Liang Dong Electrical and Computer Engineering Baylor University liang [email protected] February 23, 2017 Liang Dong (Baylor University) z-Transform Part 2 February 23, 2017 1 / 38 The z-Transform and Its Application to the Analysis of LTI Systems 1 Rational z-Transform 2 Inversion of the z-Transform 3 Analysis of LTI Systems in the z-Domain 4 Causality and Stability Liang Dong (Baylor University) z-Transform Part 2 February 23, 2017 2 / 38 Rational z-Transforms X (z) is a rational function, that is, a ratio of two polynomials in z−1 (or z). B(z) X (z) = A(z) −1 −M b0 + b1z + ··· + bM z = −1 −N a0 + a1z + ··· aN z PM b z−k = k=0 k PN −k k=0 ak z Liang Dong (Baylor University) z-Transform Part 2 February 23, 2017 3 / 38 Rational z-Transforms X (z) is a rational function, that is, a ratio of two polynomials B(z) and A(z). The polynomials can be expressed in factored forms. B(z) X (z) = A(z) b (z − z )(z − z ) ··· (z − z ) = 0 z−M+N 1 2 M a0 (z − p1)(z − p2) ··· (z − pN ) b QM (z − z ) = 0 zN−M k=1 k a QN 0 k=1(z − pk ) Liang Dong (Baylor University) z-Transform Part 2 February 23, 2017 4 / 38 Poles and Zeros The zeros of a z-transform X (z) are the values of z for which X (z) = 0. The poles of a z-transform X (z) are the values of z for which X (z) = 1. -
Section 3.7 Notes
Section 3.7 Notes Rational Functions 1 Introduction Definition • A rational function is fraction of two polynomials. 2x2 − 1 • For example, f(x) = is a rational function. 3x2 + 2x − 5 Properties of Rational Graphs • The graph of every rational function is smooth (no sharp corners) • However, many rational functions are discontinuous . In other words, the graph might have several separate \sections" to the graph, similar to the way piecewise functions look. 1 For example, remember the graph of f(x) = x : Notice how the graph is drawn in two separate pieces. Asymptotes • An asymptote to a function is a line which the function gets closer and closer to without touching. • Rational functions have two categories of asymptote: 1. vertical asymptotes 2. asymptotes which determine the end behavior - these could be either horizontal asymp- totes or slant asymptotes Vertical Asymptote Horizontal Slant Asymptote Asymptote 1 2 Vertical Asymptotes Description • A vertical asymptote of a rational function is a vertical line which the graph never crosses, but does get closer and closer to. • Rational functions can have any number of vertical asymptotes • The number of vertical asymptotes determines the number of \pieces" the graph has. Since the graph will never cross any vertical asymptotes, there will be separate pieces between and on the sides of all the vertical asymptotes. Finding Vertical Asymptotes 1. Factor the denominator. 2. Set each factor equal to zero and solve. The locations of the vertical asymptotes are nothing more than the x-values where the function is undefined. Behavior Near Vertical Asymptotes The multiplicity of the vertical asymptote determines the behavior of the graph near the asymptote: Multiplicity Behavior even The two sides of the asymptote match - they both go up or both go down. -
Introduction to Finite Fields, I
Spring 2010 Chris Christensen MAT/CSC 483 Introduction to finite fields, I Fields and rings To understand IDEA, AES, and some other modern cryptosystems, it is necessary to understand a bit about finite fields. A field is an algebraic object. The elements of a field can be added and subtracted and multiplied and divided (except by 0). Often in undergraduate mathematics courses (e.g., calculus and linear algebra) the numbers that are used come from a field. The rational a numbers = :ab , are integers and b≠ 0 form a field; rational numbers (i.e., fractions) b can be added (and subtracted) and multiplied (and divided). The real numbers form a field. The complex numbers also form a field. Number theory studies the integers . The integers do not form a field. Integers can be added and subtracted and multiplied, but integers cannot always be divided. Sure, 6 5 divided by 3 is 2; but 5 divided by 2 is not an integer; is a rational number. The 2 integers form a ring, but the rational numbers form a field. Similarly the polynomials with integer coefficients form a ring. We can add and subtract polynomials with integer coefficients, and the result will be a polynomial with integer coefficients. We can multiply polynomials with integer coefficients, and the result will be a polynomial with integer coefficients. But, we cannot always divide polynomials X 2 − 4 XX3 +−2 with integer coefficients: =X + 2 , but is not a polynomial – it is a X − 2 X 2 + 7 rational function. The polynomials with integer coefficients do not form a field, they form a ring. -
Vertical Tangents and Cusps
Section 4.7 Lecture 15 Section 4.7 Vertical and Horizontal Asymptotes; Vertical Tangents and Cusps Jiwen He Department of Mathematics, University of Houston [email protected] math.uh.edu/∼jiwenhe/Math1431 Jiwen He, University of Houston Math 1431 – Section 24076, Lecture 15 October 21, 2008 1 / 34 Section 4.7 Test 2 Test 2: November 1-4 in CASA Loggin to CourseWare to reserve your time to take the exam. Jiwen He, University of Houston Math 1431 – Section 24076, Lecture 15 October 21, 2008 2 / 34 Section 4.7 Review for Test 2 Review for Test 2 by the College Success Program. Friday, October 24 2:30–3:30pm in the basement of the library by the C-site. Jiwen He, University of Houston Math 1431 – Section 24076, Lecture 15 October 21, 2008 3 / 34 Section 4.7 Grade Information 300 points determined by exams 1, 2 and 3 100 points determined by lab work, written quizzes, homework, daily grades and online quizzes. 200 points determined by the final exam 600 points total Jiwen He, University of Houston Math 1431 – Section 24076, Lecture 15 October 21, 2008 4 / 34 Section 4.7 More Grade Information 90% and above - A at least 80% and below 90%- B at least 70% and below 80% - C at least 60% and below 70% - D below 60% - F Jiwen He, University of Houston Math 1431 – Section 24076, Lecture 15 October 21, 2008 5 / 34 Section 4.7 Online Quizzes Online Quizzes are available on CourseWare. If you fail to reach 70% during three weeks of the semester, I have the option to drop you from the course!!!. -
Calculus Terminology
AP Calculus BC Calculus Terminology Absolute Convergence Asymptote Continued Sum Absolute Maximum Average Rate of Change Continuous Function Absolute Minimum Average Value of a Function Continuously Differentiable Function Absolutely Convergent Axis of Rotation Converge Acceleration Boundary Value Problem Converge Absolutely Alternating Series Bounded Function Converge Conditionally Alternating Series Remainder Bounded Sequence Convergence Tests Alternating Series Test Bounds of Integration Convergent Sequence Analytic Methods Calculus Convergent Series Annulus Cartesian Form Critical Number Antiderivative of a Function Cavalieri’s Principle Critical Point Approximation by Differentials Center of Mass Formula Critical Value Arc Length of a Curve Centroid Curly d Area below a Curve Chain Rule Curve Area between Curves Comparison Test Curve Sketching Area of an Ellipse Concave Cusp Area of a Parabolic Segment Concave Down Cylindrical Shell Method Area under a Curve Concave Up Decreasing Function Area Using Parametric Equations Conditional Convergence Definite Integral Area Using Polar Coordinates Constant Term Definite Integral Rules Degenerate Divergent Series Function Operations Del Operator e Fundamental Theorem of Calculus Deleted Neighborhood Ellipsoid GLB Derivative End Behavior Global Maximum Derivative of a Power Series Essential Discontinuity Global Minimum Derivative Rules Explicit Differentiation Golden Spiral Difference Quotient Explicit Function Graphic Methods Differentiable Exponential Decay Greatest Lower Bound Differential -
Arxiv:1712.01752V2 [Cs.SC] 25 Oct 2018 Figure 1
Symbolic-Numeric Integration of Rational Functions Robert M Corless1, Robert HC Moir1, Marc Moreno Maza1, Ning Xie2 1Ontario Research Center for Computer Algebra, University of Western Ontario, Canada 2Huawei Technologies Corporation, Markham, ON Abstract. We consider the problem of symbolic-numeric integration of symbolic functions, focusing on rational functions. Using a hybrid method allows the stable yet efficient computation of symbolic antideriva- tives while avoiding issues of ill-conditioning to which numerical methods are susceptible. We propose two alternative methods for exact input that compute the rational part of the integral using Hermite reduction and then compute the transcendental part two different ways using a combi- nation of exact integration and efficient numerical computation of roots. The symbolic computation is done within bpas, or Basic Polynomial Al- gebra Subprograms, which is a highly optimized environment for poly- nomial computation on parallel architectures, while the numerical com- putation is done using the highly optimized multiprecision rootfinding package MPSolve. We show that both methods are forward and back- ward stable in a structured sense and away from singularities tolerance proportionality is achieved by adjusting the precision of the rootfinding tasks. 1 Introduction Hybrid symbolic-numeric integration of rational functions is interesting for sev- eral reasons. First, a formula, not a number or a computer program or subroutine, may be desired, perhaps for further analysis such as by taking asymptotics. In this case one typically wants an exact symbolic answer, and for rational func- tions this is in principle always possible. However, an exact symbolic answer may be too cluttered with algebraic numbers or lengthy rational numbers to be intelligible or easily analyzed by further symbolic manipulation. -
Apollonius of Pergaconics. Books One - Seven
APOLLONIUS OF PERGACONICS. BOOKS ONE - SEVEN INTRODUCTION A. Apollonius at Perga Apollonius was born at Perga (Περγα) on the Southern coast of Asia Mi- nor, near the modern Turkish city of Bursa. Little is known about his life before he arrived in Alexandria, where he studied. Certain information about Apollonius’ life in Asia Minor can be obtained from his preface to Book 2 of Conics. The name “Apollonius”(Apollonius) means “devoted to Apollo”, similarly to “Artemius” or “Demetrius” meaning “devoted to Artemis or Demeter”. In the mentioned preface Apollonius writes to Eudemus of Pergamum that he sends him one of the books of Conics via his son also named Apollonius. The coincidence shows that this name was traditional in the family, and in all prob- ability Apollonius’ ancestors were priests of Apollo. Asia Minor during many centuries was for Indo-European tribes a bridge to Europe from their pre-fatherland south of the Caspian Sea. The Indo-European nation living in Asia Minor in 2nd and the beginning of the 1st millennia B.C. was usually called Hittites. Hittites are mentioned in the Bible and in Egyptian papyri. A military leader serving under the Biblical king David was the Hittite Uriah. His wife Bath- sheba, after his death, became the wife of king David and the mother of king Solomon. Hittites had a cuneiform writing analogous to the Babylonian one and hi- eroglyphs analogous to Egyptian ones. The Czech historian Bedrich Hrozny (1879-1952) who has deciphered Hittite cuneiform writing had established that the Hittite language belonged to the Western group of Indo-European languages [Hro]. -
Lecture 8 - the Extended Complex Plane Cˆ, Rational Functions, M¨Obius Transformations
Math 207 - Spring '17 - Fran¸coisMonard 1 Lecture 8 - The extended complex plane C^, rational functions, M¨obius transformations Material: [G]. [SS, Ch.3 Sec. 3] 1 The purpose of this lecture is to \compactify" C by adjoining to it a point at infinity , and to extend to concept of analyticity there. Let us first define: a neighborhood of infinity U is the complement of a closed, bounded set. A \basis of neighborhoods" is given by complements of closed disks of the form Uz0,ρ = C − Dρ(z0) = fjz − z0j > ρg; z0 2 C; ρ > 0: Definition 1. For U a nbhd of 1, the function f : U ! C has a limit at infinity iff there exists L 2 C such that for every " > 0, there exists R > 0 such that for any jzj > R, we have jf(z)−Lj < ". 1 We write limz!1 f(z) = L. Equivalently, limz!1 f(z) = L if and only if limz!0 f z = L. With this concept, the algebraic limit rules hold in the same way that they hold at finite points when limits are finite. 1 Example 1. • limz!1 z = 0. z2+1 1 • limz!1 (z−1)(3z+7) = 3 . z 1 • limz!1 e does not exist (this is because e z has an essential singularity at z = 0). A way 1 0 1 to prove this is that both sequences zn = 2nπi and zn = 2πi(n+1=2) converge to zero, while the 1 1 0 sequences e zn and e zn converge to different limits, 1 and 0 respectively. -
Chapter 2 Complex Analysis
Chapter 2 Complex Analysis In this part of the course we will study some basic complex analysis. This is an extremely useful and beautiful part of mathematics and forms the basis of many techniques employed in many branches of mathematics and physics. We will extend the notions of derivatives and integrals, familiar from calculus, to the case of complex functions of a complex variable. In so doing we will come across analytic functions, which form the centerpiece of this part of the course. In fact, to a large extent complex analysis is the study of analytic functions. After a brief review of complex numbers as points in the complex plane, we will ¯rst discuss analyticity and give plenty of examples of analytic functions. We will then discuss complex integration, culminating with the generalised Cauchy Integral Formula, and some of its applications. We then go on to discuss the power series representations of analytic functions and the residue calculus, which will allow us to compute many real integrals and in¯nite sums very easily via complex integration. 2.1 Analytic functions In this section we will study complex functions of a complex variable. We will see that di®erentiability of such a function is a non-trivial property, giving rise to the concept of an analytic function. We will then study many examples of analytic functions. In fact, the construction of analytic functions will form a basic leitmotif for this part of the course. 2.1.1 The complex plane We already discussed complex numbers briefly in Section 1.3.5. -
CYCLIC RESULTANTS 1. Introduction the M-Th Cyclic Resultant of A
CYCLIC RESULTANTS CHRISTOPHER J. HILLAR Abstract. We characterize polynomials having the same set of nonzero cyclic resultants. Generically, for a polynomial f of degree d, there are exactly 2d−1 distinct degree d polynomials with the same set of cyclic resultants as f. How- ever, in the generic monic case, degree d polynomials are uniquely determined by their cyclic resultants. Moreover, two reciprocal (\palindromic") polyno- mials giving rise to the same set of nonzero cyclic resultants are equal. In the process, we also prove a unique factorization result in semigroup algebras involving products of binomials. Finally, we discuss how our results yield algo- rithms for explicit reconstruction of polynomials from their cyclic resultants. 1. Introduction The m-th cyclic resultant of a univariate polynomial f 2 C[x] is m rm = Res(f; x − 1): We are primarily interested here in the fibers of the map r : C[x] ! CN given by 1 f 7! (rm)m=0. In particular, what are the conditions for two polynomials to give rise to the same set of cyclic resultants? For technical reasons, we will only consider polynomials f that do not have a root of unity as a zero. With this restriction, a polynomial will map to a set of all nonzero cyclic resultants. Our main result gives a complete answer to this question. Theorem 1.1. Let f and g be polynomials in C[x]. Then, f and g generate the same sequence of nonzero cyclic resultants if and only if there exist u; v 2 C[x] with u(0) 6= 0 and nonnegative integers l1; l2 such that deg(u) ≡ l2 − l1 (mod 2), and f(x) = (−1)l2−l1 xl1 v(x)u(x−1)xdeg(u) g(x) = xl2 v(x)u(x): Remark 1.2. -
Rational Functions
Chapter 4 Rational Functions 4.1 Introduction to Rational Functions If we add, subtract or multiply polynomial functions according to the function arithmetic rules defined in Section 1.5, we will produce another polynomial function. If, on the other hand, we divide two polynomial functions, the result may not be a polynomial. In this chapter we study rational functions - functions which are ratios of polynomials. Definition 4.1. A rational function is a function which is the ratio of polynomial functions. Said differently, r is a rational function if it is of the form p(x) r(x) = ; q(x) where p and q are polynomial functions.a aAccording to this definition, all polynomial functions are also rational functions. (Take q(x) = 1). As we recall from Section 1.4, we have domain issues anytime the denominator of a fraction is zero. In the example below, we review this concept as well as some of the arithmetic of rational expressions. p(x) Example 4.1.1. Find the domain of the following rational functions. Write them in the form q(x) for polynomial functions p and q and simplify. 2x − 1 3 1. f(x) = 2. g(x) = 2 − x + 1 x + 1 2x2 − 1 3x − 2 2x2 − 1 3x − 2 3. h(x) = − 4. r(x) = ÷ x2 − 1 x2 − 1 x2 − 1 x2 − 1 Solution. 1. To find the domain of f, we proceed as we did in Section 1.4: we find the zeros of the denominator and exclude them from the domain. Setting x + 1 = 0 results in x = −1.