Mathematics Glossary
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Inverse of Exponential Functions Are Logarithmic Functions
Math Instructional Framework Full Name Math III Unit 3 Lesson 2 Time Frame Unit Name Logarithmic Functions as Inverses of Exponential Functions Learning Task/Topics/ Task 2: How long Does It Take? Themes Task 3: The Population of Exponentia Task 4: Modeling Natural Phenomena on Earth Culminating Task: Traveling to Exponentia Standards and Elements MM3A2. Students will explore logarithmic functions as inverses of exponential functions. c. Define logarithmic functions as inverses of exponential functions. Lesson Essential Questions How can you graph the inverse of an exponential function? Activator PROBLEM 2.Task 3: The Population of Exponentia (Problem 1 could be completed prior) Work Session Inverse of Exponential Functions are Logarithmic Functions A Graph the inverse of exponential functions. B Graph logarithmic functions. See Notes Below. VOCABULARY Asymptote: A line or curve that describes the end behavior of the graph. A graph never crosses a vertical asymptote but it may cross a horizontal or oblique asymptote. Common logarithm: A logarithm with a base of 10. A common logarithm is the power, a, such that 10a = b. The common logarithm of x is written log x. For example, log 100 = 2 because 102 = 100. Exponential functions: A function of the form y = a·bx where a > 0 and either 0 < b < 1 or b > 1. Logarithmic functions: A function of the form y = logbx, with b 1 and b and x both positive. A logarithmic x function is the inverse of an exponential function. The inverse of y = b is y = logbx. Logarithm: The logarithm base b of a number x, logbx, is the power to which b must be raised to equal x. -
7: Inner Products, Fourier Series, Convolution
7: FOURIER SERIES STEVEN HEILMAN Contents 1. Review 1 2. Introduction 1 3. Periodic Functions 2 4. Inner Products on Periodic Functions 3 5. Trigonometric Polynomials 5 6. Periodic Convolutions 7 7. Fourier Inversion and Plancherel Theorems 10 8. Appendix: Notation 13 1. Review Exercise 1.1. Let (X; h·; ·i) be a (real or complex) inner product space. Define k·k : X ! [0; 1) by kxk := phx; xi. Then (X; k·k) is a normed linear space. Consequently, if we define d: X × X ! [0; 1) by d(x; y) := ph(x − y); (x − y)i, then (X; d) is a metric space. Exercise 1.2 (Cauchy-Schwarz Inequality). Let (X; h·; ·i) be a complex inner product space. Let x; y 2 X. Then jhx; yij ≤ hx; xi1=2hy; yi1=2: Exercise 1.3. Let (X; h·; ·i) be a complex inner product space. Let x; y 2 X. As usual, let kxk := phx; xi. Prove Pythagoras's theorem: if hx; yi = 0, then kx + yk2 = kxk2 + kyk2. 1 Theorem 1.4 (Weierstrass M-test). Let (X; d) be a metric space and let (fj)j=1 be a sequence of bounded real-valued continuous functions on X such that the series (of real num- P1 P1 bers) j=1 kfjk1 is absolutely convergent. Then the series j=1 fj converges uniformly to some continuous function f : X ! R. 2. Introduction A general problem in analysis is to approximate a general function by a series that is relatively easy to describe. With the Weierstrass Approximation theorem, we saw that it is possible to achieve this goal by approximating compactly supported continuous functions by polynomials. -
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. -
Fourier Series
Academic Press Encyclopedia of Physical Science and Technology Fourier Series James S. Walker Department of Mathematics University of Wisconsin–Eau Claire Eau Claire, WI 54702–4004 Phone: 715–836–3301 Fax: 715–836–2924 e-mail: [email protected] 1 2 Encyclopedia of Physical Science and Technology I. Introduction II. Historical background III. Definition of Fourier series IV. Convergence of Fourier series V. Convergence in norm VI. Summability of Fourier series VII. Generalized Fourier series VIII. Discrete Fourier series IX. Conclusion GLOSSARY ¢¤£¦¥¨§ Bounded variation: A function has bounded variation on a closed interval ¡ ¢ if there exists a positive constant © such that, for all finite sets of points "! "! $#&% (' #*) © ¥ , the inequality is satisfied. Jordan proved that a function has bounded variation if and only if it can be expressed as the difference of two non-decreasing functions. Countably infinite set: A set is countably infinite if it can be put into one-to-one £0/"£ correspondence with the set of natural numbers ( +,£¦-.£ ). Examples: The integers and the rational numbers are countably infinite sets. "! "!;: # # 123547698 Continuous function: If , then the function is continuous at the point : . Such a point is called a continuity point for . A function which is continuous at all points is simply referred to as continuous. Lebesgue measure zero: A set < of real numbers is said to have Lebesgue measure ! $#¨CED B ¢ £¦¥ zero if, for each =?>A@ , there exists a collection of open intervals such ! ! D D J# K% $#L) ¢ £¦¥ ¥ ¢ = that <GFIH and . Examples: All finite sets, and all countably infinite sets, have Lebesgue measure zero. "! "! % # % # Odd and even functions: A function is odd if for all in its "! "! % # # domain. -
Circle Theorems
Circle theorems A LEVEL LINKS Scheme of work: 2b. Circles – equation of a circle, geometric problems on a grid Key points • A chord is a straight line joining two points on the circumference of a circle. So AB is a chord. • A tangent is a straight line that touches the circumference of a circle at only one point. The angle between a tangent and the radius is 90°. • Two tangents on a circle that meet at a point outside the circle are equal in length. So AC = BC. • The angle in a semicircle is a right angle. So angle ABC = 90°. • When two angles are subtended by the same arc, the angle at the centre of a circle is twice the angle at the circumference. So angle AOB = 2 × angle ACB. • Angles subtended by the same arc at the circumference are equal. This means that angles in the same segment are equal. So angle ACB = angle ADB and angle CAD = angle CBD. • A cyclic quadrilateral is a quadrilateral with all four vertices on the circumference of a circle. Opposite angles in a cyclic quadrilateral total 180°. So x + y = 180° and p + q = 180°. • The angle between a tangent and chord is equal to the angle in the alternate segment, this is known as the alternate segment theorem. So angle BAT = angle ACB. Examples Example 1 Work out the size of each angle marked with a letter. Give reasons for your answers. Angle a = 360° − 92° 1 The angles in a full turn total 360°. = 268° as the angles in a full turn total 360°. -
5.7 Inverses and Radical Functions Finding the Inverse Of
SECTION 5.7 iNverses ANd rAdicAl fuNctioNs 435 leARnIng ObjeCTIveS In this section, you will: • Find the inverse of an invertible polynomial function. • Restrict the domain to find the inverse of a polynomial function. 5.7 InveRSeS And RAdICAl FUnCTIOnS A mound of gravel is in the shape of a cone with the height equal to twice the radius. Figure 1 The volume is found using a formula from elementary geometry. __1 V = πr 2 h 3 __1 = πr 2(2r) 3 __2 = πr 3 3 We have written the volume V in terms of the radius r. However, in some cases, we may start out with the volume and want to find the radius. For example: A customer purchases 100 cubic feet of gravel to construct a cone shape mound with a height twice the radius. What are the radius and height of the new cone? To answer this question, we use the formula ____ 3 3V r = ___ √ 2π This function is the inverse of the formula for V in terms of r. In this section, we will explore the inverses of polynomial and rational functions and in particular the radical functions we encounter in the process. Finding the Inverse of a Polynomial Function Two functions f and g are inverse functions if for every coordinate pair in f, (a, b), there exists a corresponding coordinate pair in the inverse function, g, (b, a). In other words, the coordinate pairs of the inverse functions have the input and output interchanged. Only one-to-one functions have inverses. Recall that a one-to-one function has a unique output value for each input value and passes the horizontal line test. -
Angles ANGLE Topics • Coterminal Angles • Defintion of an Angle
Angles ANGLE Topics • Coterminal Angles • Defintion of an angle • Decimal degrees to degrees, minutes, seconds by hand using the TI-82 or TI-83 Plus • Degrees, seconds, minutes changed to decimal degree by hand using the TI-82 or TI-83 Plus • Standard position of an angle • Positive and Negative angles ___________________________________________________________________________ Definition: Angle An angle is created when a half-ray (the initial side of the angle) is drawn out of a single point (the vertex of the angle) and the ray is rotated around the point to another location (becoming the terminal side of the angle). An angle is created when a half-ray (initial side of angle) A: vertex point of angle is drawn out of a single point (vertex) AB: Initial side of angle. and the ray is rotated around the point to AC: Terminal side of angle another location (becoming the terminal side of the angle). Hence angle A is created (also called angle BAC) STANDARD POSITION An angle is in "standard position" when the vertex is at the origin and the initial side of the angle is along the positive x-axis. Recall: polynomials in algebra have a standard form (all the terms have to be listed with the term having the highest exponent first). In trigonometry, there is a standard position for angles. In this way, we are all talking about the same thing and are not trying to guess if your math solution and my math solution are the same. Not standard position. Not standard position. This IS standard position. Initial side not along Initial side along negative Initial side IS along the positive x-axis. -
Contentscontents 2323 Fourier Series
ContentsContents 2323 Fourier Series 23.1 Periodic Functions 2 23.2 Representing Periodic Functions by Fourier Series 9 23.3 Even and Odd Functions 30 23.4 Convergence 40 23.5 Half-range Series 46 23.6 The Complex Form 53 23.7 An Application of Fourier Series 68 Learning outcomes In this Workbook you will learn how to express a periodic signal f(t) in a series of sines and cosines. You will learn how to simplify the calculations if the signal happens to be an even or an odd function. You will learn some brief facts relating to the convergence of the Fourier series. You will learn how to approximate a non-periodic signal by a Fourier series. You will learn how to re-express a standard Fourier series in complex form which paves the way for a later examination of Fourier transforms. Finally you will learn about some simple applications of Fourier series. Periodic Functions 23.1 Introduction You should already know how to take a function of a single variable f(x) and represent it by a power series in x about any point x0 of interest. Such a series is known as a Taylor series or Taylor expansion or, if x0 = 0, as a Maclaurin series. This topic was firs met in 16. Such an expansion is only possible if the function is sufficiently smooth (that is, if it can be differentiated as often as required). Geometrically this means that there are no jumps or spikes in the curve y = f(x) near the point of expansion. -
On the Real Projections of Zeros of Almost Periodic Functions
ON THE REAL PROJECTIONS OF ZEROS OF ALMOST PERIODIC FUNCTIONS J.M. SEPULCRE AND T. VIDAL Abstract. This paper deals with the set of the real projections of the zeros of an arbitrary almost periodic function defined in a vertical strip U. It pro- vides practical results in order to determine whether a real number belongs to the closure of such a set. Its main result shows that, in the case that the Fourier exponents {λ1, λ2, λ3,...} of an almost periodic function are linearly independent over the rational numbers, such a set has no isolated points in U. 1. Introduction The theory of almost periodic functions, which was created and developed in its main features by H. Bohr during the 1920’s, opened a way to study a wide class of trigonometric series of the general type and even exponential series. This theory shortly acquired numerous applications to various areas of mathematics, from harmonic analysis to differential equations. In the case of the functions that are defined on the real numbers, the notion of almost periodicity is a generalization of purely periodic functions and, in fact, as in classical Fourier analysis, any almost periodic function is associated with a Fourier series with real frequencies. Let us briefly recall some notions concerning the theory of the almost periodic functions of a complex variable, which was theorized in [4] (see also [3, 5, 8, 11]). A function f(s), s = σ + it, analytic in a vertical strip U = {s = σ + it ∈ C : α< σ<β} (−∞ ≤ α<β ≤ ∞), is called almost periodic in U if to any ε > 0 there exists a number l = l(ε) such that each interval t0 <t<t0 + l of length l contains a number τ satisfying |f(s + iτ) − f(s)|≤ ε ∀s ∈ U. -
Almost Periodic Sequences and Functions with Given Values
ARCHIVUM MATHEMATICUM (BRNO) Tomus 47 (2011), 1–16 ALMOST PERIODIC SEQUENCES AND FUNCTIONS WITH GIVEN VALUES Michal Veselý Abstract. We present a method for constructing almost periodic sequences and functions with values in a metric space. Applying this method, we find almost periodic sequences and functions with prescribed values. Especially, for any totally bounded countable set X in a metric space, it is proved the existence of an almost periodic sequence {ψk}k∈Z such that {ψk; k ∈ Z} = X and ψk = ψk+lq(k), l ∈ Z for all k and some q(k) ∈ N which depends on k. 1. Introduction The aim of this paper is to construct almost periodic sequences and functions which attain values in a metric space. More precisely, our aim is to find almost periodic sequences and functions whose ranges contain or consist of arbitrarily given subsets of the metric space satisfying certain conditions. We are motivated by the paper [3] where a similar problem is investigated for real-valued sequences. In that paper, using an explicit construction, it is shown that, for any bounded countable set of real numbers, there exists an almost periodic sequence whose range is this set and which attains each value in this set periodically. We will extend this result to sequences attaining values in any metric space. Concerning almost periodic sequences with indices k ∈ N (or asymptotically almost periodic sequences), we refer to [4] where it is proved that, for any precompact sequence {xk}k∈N in a metric space X , there exists a permutation P of the set of positive integers such that the sequence {xP (k)}k∈N is almost periodic. -
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 -
Fourier Transform for Mean Periodic Functions
Annales Univ. Sci. Budapest., Sect. Comp. 35 (2011) 267–283 FOURIER TRANSFORM FOR MEAN PERIODIC FUNCTIONS L´aszl´oSz´ekelyhidi (Debrecen, Hungary) Dedicated to the 60th birthday of Professor Antal J´arai Abstract. Mean periodic functions are natural generalizations of periodic functions. There are different transforms - like Fourier transforms - defined for these types of functions. In this note we introduce some transforms and compare them with the usual Fourier transform. 1. Introduction In this paper C(R) denotes the locally convex topological vector space of all continuous complex valued functions on the reals, equipped with the linear operations and the topology of uniform convergence on compact sets. Any closed translation invariant subspace of C(R)iscalledavariety. The smallest variety containing a given f in C(R)iscalledthevariety generated by f and it is denoted by τ(f). If this is different from C(R), then f is called mean periodic. In other words, a function f in C(R) is mean periodic if and only if there exists a nonzero continuous linear functional μ on C(R) such that (1) f ∗ μ =0 2000 Mathematics Subject Classification: 42A16, 42A38. Key words and phrases: Mean periodic function, Fourier transform, Carleman transform. The research was supported by the Hungarian National Foundation for Scientific Research (OTKA), Grant No. NK-68040. 268 L. Sz´ekelyhidi holds. In this case sometimes we say that f is mean periodic with respect to μ. As any continuous linear functional on C(R) can be identified with a compactly supported complex Borel measure on R, equation (1) has the form (2) f(x − y) dμ(y)=0 for each x in R.