Glossary from Math Analysis
Total Page:16
File Type:pdf, Size:1020Kb
Load more
Recommended publications
-
Chapter 11. Three Dimensional Analytic Geometry and Vectors
Chapter 11. Three dimensional analytic geometry and vectors. Section 11.5 Quadric surfaces. Curves in R2 : x2 y2 ellipse + =1 a2 b2 x2 y2 hyperbola − =1 a2 b2 parabola y = ax2 or x = by2 A quadric surface is the graph of a second degree equation in three variables. The most general such equation is Ax2 + By2 + Cz2 + Dxy + Exz + F yz + Gx + Hy + Iz + J =0, where A, B, C, ..., J are constants. By translation and rotation the equation can be brought into one of two standard forms Ax2 + By2 + Cz2 + J =0 or Ax2 + By2 + Iz =0 In order to sketch the graph of a quadric surface, it is useful to determine the curves of intersection of the surface with planes parallel to the coordinate planes. These curves are called traces of the surface. Ellipsoids The quadric surface with equation x2 y2 z2 + + =1 a2 b2 c2 is called an ellipsoid because all of its traces are ellipses. 2 1 x y 3 2 1 z ±1 ±2 ±3 ±1 ±2 The six intercepts of the ellipsoid are (±a, 0, 0), (0, ±b, 0), and (0, 0, ±c) and the ellipsoid lies in the box |x| ≤ a, |y| ≤ b, |z| ≤ c Since the ellipsoid involves only even powers of x, y, and z, the ellipsoid is symmetric with respect to each coordinate plane. Example 1. Find the traces of the surface 4x2 +9y2 + 36z2 = 36 1 in the planes x = k, y = k, and z = k. Identify the surface and sketch it. Hyperboloids Hyperboloid of one sheet. The quadric surface with equations x2 y2 z2 1. -
Niobrara County School District #1 Curriculum Guide
NIOBRARA COUNTY SCHOOL DISTRICT #1 CURRICULUM GUIDE th SUBJECT: Math Algebra II TIMELINE: 4 quarter Domain: Student Friendly Level of Resource Academic Standard: Learning Objective Thinking Correlation/Exemplar Vocabulary [Assessment] [Mathematical Practices] Domain: Perform operations on matrices and use matrices in applications. Standards: N-VM.6.Use matrices to I can represent and Application Pearson Alg. II Textbook: Matrix represent and manipulated data, e.g., manipulate data to represent --Lesson 12-2 p. 772 (Matrices) to represent payoffs or incidence data. M --Concept Byte 12-2 p. relationships in a network. 780 Data --Lesson 12-5 p. 801 [Assessment]: --Concept Byte 12-2 p. 780 [Mathematical Practices]: Niobrara County School District #1, Fall 2012 Page 1 NIOBRARA COUNTY SCHOOL DISTRICT #1 CURRICULUM GUIDE th SUBJECT: Math Algebra II TIMELINE: 4 quarter Domain: Student Friendly Level of Resource Academic Standard: Learning Objective Thinking Correlation/Exemplar Vocabulary [Assessment] [Mathematical Practices] Domain: Perform operations on matrices and use matrices in applications. Standards: N-VM.7. Multiply matrices I can multiply matrices by Application Pearson Alg. II Textbook: Scalars by scalars to produce new matrices, scalars to produce new --Lesson 12-2 p. 772 e.g., as when all of the payoffs in a matrices. M --Lesson 12-5 p. 801 game are doubled. [Assessment]: [Mathematical Practices]: Domain: Perform operations on matrices and use matrices in applications. Standards:N-VM.8.Add, subtract and I can perform operations on Knowledge Pearson Alg. II Common Matrix multiply matrices of appropriate matrices and reiterate the Core Textbook: Dimensions dimensions. limitations on matrix --Lesson 12-1p. 764 [Assessment]: dimensions. -
An Appreciation of Euler's Formula
Rose-Hulman Undergraduate Mathematics Journal Volume 18 Issue 1 Article 17 An Appreciation of Euler's Formula Caleb Larson North Dakota State University Follow this and additional works at: https://scholar.rose-hulman.edu/rhumj Recommended Citation Larson, Caleb (2017) "An Appreciation of Euler's Formula," Rose-Hulman Undergraduate Mathematics Journal: Vol. 18 : Iss. 1 , Article 17. Available at: https://scholar.rose-hulman.edu/rhumj/vol18/iss1/17 Rose- Hulman Undergraduate Mathematics Journal an appreciation of euler's formula Caleb Larson a Volume 18, No. 1, Spring 2017 Sponsored by Rose-Hulman Institute of Technology Department of Mathematics Terre Haute, IN 47803 [email protected] a scholar.rose-hulman.edu/rhumj North Dakota State University Rose-Hulman Undergraduate Mathematics Journal Volume 18, No. 1, Spring 2017 an appreciation of euler's formula Caleb Larson Abstract. For many mathematicians, a certain characteristic about an area of mathematics will lure him/her to study that area further. That characteristic might be an interesting conclusion, an intricate implication, or an appreciation of the impact that the area has upon mathematics. The particular area that we will be exploring is Euler's Formula, eix = cos x + i sin x, and as a result, Euler's Identity, eiπ + 1 = 0. Throughout this paper, we will develop an appreciation for Euler's Formula as it combines the seemingly unrelated exponential functions, imaginary numbers, and trigonometric functions into a single formula. To appreciate and further understand Euler's Formula, we will give attention to the individual aspects of the formula, and develop the necessary tools to prove it. -
Complex Eigenvalues
Quantitative Understanding in Biology Module III: Linear Difference Equations Lecture II: Complex Eigenvalues Introduction In the previous section, we considered the generalized two- variable system of linear difference equations, and showed that the eigenvalues of these systems are given by the equation… ± 2 4 = 1,2 2 √ − …where b = (a11 + a22), c=(a22 ∙ a11 – a12 ∙ a21), and ai,j are the elements of the 2 x 2 matrix that define the linear system. Inspecting this relation shows that it is possible for the eigenvalues of such a system to be complex numbers. Because our plants and seeds model was our first look at these systems, it was carefully constructed to avoid this complication [exercise: can you show that http://www.xkcd.org/179 this model cannot produce complex eigenvalues]. However, many systems of biological interest do have complex eigenvalues, so it is important that we understand how to deal with and interpret them. We’ll begin with a review of the basic algebra of complex numbers, and then consider their meaning as eigenvalues of dynamical systems. A Review of Complex Numbers You may recall that complex numbers can be represented with the notation a+bi, where a is the real part of the complex number, and b is the imaginary part. The symbol i denotes 1 (recall i2 = -1, i3 = -i and i4 = +1). Hence, complex numbers can be thought of as points on a complex plane, which has real √− and imaginary axes. In some disciplines, such as electrical engineering, you may see 1 represented by the symbol j. √− This geometric model of a complex number suggests an alternate, but equivalent, representation. -
Newton and Leibniz: the Development of Calculus Isaac Newton (1642-1727)
Newton and Leibniz: The development of calculus Isaac Newton (1642-1727) Isaac Newton was born on Christmas day in 1642, the same year that Galileo died. This coincidence seemed to be symbolic and in many ways, Newton developed both mathematics and physics from where Galileo had left off. A few months before his birth, his father died and his mother had remarried and Isaac was raised by his grandmother. His uncle recognized Newton’s mathematical abilities and suggested he enroll in Trinity College in Cambridge. Newton at Trinity College At Trinity, Newton keenly studied Euclid, Descartes, Kepler, Galileo, Viete and Wallis. He wrote later to Robert Hooke, “If I have seen farther, it is because I have stood on the shoulders of giants.” Shortly after he received his Bachelor’s degree in 1665, Cambridge University was closed due to the bubonic plague and so he went to his grandmother’s house where he dived deep into his mathematics and physics without interruption. During this time, he made four major discoveries: (a) the binomial theorem; (b) calculus ; (c) the law of universal gravitation and (d) the nature of light. The binomial theorem, as we discussed, was of course known to the Chinese, the Indians, and was re-discovered by Blaise Pascal. But Newton’s innovation is to discuss it for fractional powers. The binomial theorem Newton’s notation in many places is a bit clumsy and he would write his version of the binomial theorem as: In modern notation, the left hand side is (P+PQ)m/n and the first term on the right hand side is Pm/n and the other terms are: The binomial theorem as a Taylor series What we see here is the Taylor series expansion of the function (1+Q)m/n. -
Automatic Estimation of Sphere Centers from Images of Calibrated Cameras
Automatic Estimation of Sphere Centers from Images of Calibrated Cameras Levente Hajder 1 , Tekla Toth´ 1 and Zoltan´ Pusztai 1 1Department of Algorithms and Their Applications, Eotv¨ os¨ Lorand´ University, Pazm´ any´ Peter´ stny. 1/C, Budapest, Hungary, H-1117 fhajder,tekla.toth,[email protected] Keywords: Ellipse Detection, Spatial Estimation, Calibrated Camera, 3D Computer Vision Abstract: Calibration of devices with different modalities is a key problem in robotic vision. Regular spatial objects, such as planes, are frequently used for this task. This paper deals with the automatic detection of ellipses in camera images, as well as to estimate the 3D position of the spheres corresponding to the detected 2D ellipses. We propose two novel methods to (i) detect an ellipse in camera images and (ii) estimate the spatial location of the corresponding sphere if its size is known. The algorithms are tested both quantitatively and qualitatively. They are applied for calibrating the sensor system of autonomous cars equipped with digital cameras, depth sensors and LiDAR devices. 1 INTRODUCTION putation and memory costs. Probabilistic Hough Transform (PHT) is a variant of the classical HT: it Ellipse fitting in images has been a long researched randomly selects a small subset of the edge points problem in computer vision for many decades (Prof- which is used as input for HT (Kiryati et al., 1991). fitt, 1982). Ellipses can be used for camera calibra- The 5D parameter space can be divided into two tion (Ji and Hu, 2001; Heikkila, 2000), estimating the pieces. First, the ellipse center is estimated, then the position of parts in an assembly system (Shin et al., remaining three parameters are found in the second 2011) or for defect detection in printed circuit boards stage (Yuen et al., 1989; Tsuji and Matsumoto, 1978). -
Mathematics (MATH)
Course Descriptions MATH 1080 QL MATH 1210 QL Mathematics (MATH) Precalculus Calculus I 5 5 MATH 100R * Prerequisite(s): Within the past two years, * Prerequisite(s): One of the following within Math Leap one of the following: MAT 1000 or MAT 1010 the past two years: (MATH 1050 or MATH 1 with a grade of B or better or an appropriate 1055) and MATH 1060, each with a grade of Is part of UVU’s math placement process; for math placement score. C or higher; OR MATH 1080 with a grade of C students who desire to review math topics Is an accelerated version of MATH 1050 or higher; OR appropriate placement by math in order to improve placement level before and MATH 1060. Includes functions and placement test. beginning a math course. Addresses unique their graphs including polynomial, rational, Covers limits, continuity, differentiation, strengths and weaknesses of students, by exponential, logarithmic, trigonometric, and applications of differentiation, integration, providing group problem solving activities along inverse trigonometric functions. Covers and applications of integration, including with an individual assessment and study inequalities, systems of linear and derivatives and integrals of polynomial plan for mastering target material. Requires nonlinear equations, matrices, determinants, functions, rational functions, exponential mandatory class attendance and a minimum arithmetic and geometric sequences, the functions, logarithmic functions, trigonometric number of hours per week logged into a Binomial Theorem, the unit circle, right functions, inverse trigonometric functions, and preparation module, with progress monitored triangle trigonometry, trigonometric equations, hyperbolic functions. Is a prerequisite for by a mentor. May be repeated for a maximum trigonometric identities, the Law of Sines, the calculus-based sciences. -
Think Python
Think Python How to Think Like a Computer Scientist 2nd Edition, Version 2.2.18 Think Python How to Think Like a Computer Scientist 2nd Edition, Version 2.2.18 Allen Downey Green Tea Press Needham, Massachusetts Copyright © 2015 Allen Downey. Green Tea Press 9 Washburn Ave Needham MA 02492 Permission is granted to copy, distribute, and/or modify this document under the terms of the Creative Commons Attribution-NonCommercial 3.0 Unported License, which is available at http: //creativecommons.org/licenses/by-nc/3.0/. The original form of this book is LATEX source code. Compiling this LATEX source has the effect of gen- erating a device-independent representation of a textbook, which can be converted to other formats and printed. http://www.thinkpython2.com The LATEX source for this book is available from Preface The strange history of this book In January 1999 I was preparing to teach an introductory programming class in Java. I had taught it three times and I was getting frustrated. The failure rate in the class was too high and, even for students who succeeded, the overall level of achievement was too low. One of the problems I saw was the books. They were too big, with too much unnecessary detail about Java, and not enough high-level guidance about how to program. And they all suffered from the trap door effect: they would start out easy, proceed gradually, and then somewhere around Chapter 5 the bottom would fall out. The students would get too much new material, too fast, and I would spend the rest of the semester picking up the pieces. -
Introduction Into Quaternions for Spacecraft Attitude Representation
Introduction into quaternions for spacecraft attitude representation Dipl. -Ing. Karsten Groÿekatthöfer, Dr. -Ing. Zizung Yoon Technical University of Berlin Department of Astronautics and Aeronautics Berlin, Germany May 31, 2012 Abstract The purpose of this paper is to provide a straight-forward and practical introduction to quaternion operation and calculation for rigid-body attitude representation. Therefore the basic quaternion denition as well as transformation rules and conversion rules to or from other attitude representation parameters are summarized. The quaternion computation rules are supported by practical examples to make each step comprehensible. 1 Introduction Quaternions are widely used as attitude represenation parameter of rigid bodies such as space- crafts. This is due to the fact that quaternion inherently come along with some advantages such as no singularity and computationally less intense compared to other attitude parameters such as Euler angles or a direction cosine matrix. Mainly, quaternions are used to • Parameterize a spacecraft's attitude with respect to reference coordinate system, • Propagate the attitude from one moment to the next by integrating the spacecraft equa- tions of motion, • Perform a coordinate transformation: e.g. calculate a vector in body xed frame from a (by measurement) known vector in inertial frame. However, dierent references use several notations and rules to represent and handle attitude in terms of quaternions, which might be confusing for newcomers [5], [4]. Therefore this article gives a straight-forward and clearly notated introduction into the subject of quaternions for attitude representation. The attitude of a spacecraft is its rotational orientation in space relative to a dened reference coordinate system. -
Natural Domain of a Function • Range Calculations Table of Contents (Continued)
~ THE UNIVERSITY OF AKRON w Mathematics and Computer Science calculus Article: Functions menu Directory • Table of Contents • Begin tutorial on Functions • Index Copyright c 1995{1998 D. P. Story Last Revision Date: 11/6/1998 Functions Table of Contents 1. Introduction 2. The Concept of a Function 2.1. Constructing Functions • The Use of Algebraic Expressions • Piecewise Definitions • Descriptive or Conceptual Methods 2.2. Evaluation Issues • Numerical Evaluation • Symbolic Evalulation 2.3. What's in a Name • The \Standard" Way • Functions Named by the Depen- dent Variable • Descriptive Naming • Famous Functions 2.4. Models for Functions • A Function as a Mapping • Venn Diagram of a Function • A Function as a Black Box 2.5. Calculating the Domain and Range • The Natural Domain of a Function • Range Calculations Table of Contents (continued) 2.6. Recognizing Functions • Interpreting the Terminology • The Vertical Line Test 3. Graphing: First Principles 4. Methods of Combining Functions 4.1. The Algebra of Functions 4.2. The Composition of Functions 4.3. Shifting and Rescaling • Horizontal Shifting • Vertical Shifting • Rescaling 5. Classification of Functions • Polynomial Functions • Rational Functions • Algebraic Functions 1. Introduction In the world of Mathematics one of the most common creatures en- countered is the function. It is important to understand the idea of a function if you want to gain a thorough understanding of Calculus. Science concerns itself with the discovery of physical or scientific truth. In a portion of these investigations, researchers (or engineers) attempt to discern relationships between physical quantities of interest. There are many ways of interpreting the meaning of the word \relation- ships," but in Calculus we are most often concerned with functional relationships. -
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°. -
Curl, Divergence and Laplacian
Curl, Divergence and Laplacian What to know: 1. The definition of curl and it two properties, that is, theorem 1, and be able to predict qualitatively how the curl of a vector field behaves from a picture. 2. The definition of divergence and it two properties, that is, if div F~ 6= 0 then F~ can't be written as the curl of another field, and be able to tell a vector field of clearly nonzero,positive or negative divergence from the picture. 3. Know the definition of the Laplace operator 4. Know what kind of objects those operator take as input and what they give as output. The curl operator Let's look at two plots of vector fields: Figure 1: The vector field Figure 2: The vector field h−y; x; 0i: h1; 1; 0i We can observe that the second one looks like it is rotating around the z axis. We'd like to be able to predict this kind of behavior without having to look at a picture. We also promised to find a criterion that checks whether a vector field is conservative in R3. Both of those goals are accomplished using a tool called the curl operator, even though neither of those two properties is exactly obvious from the definition we'll give. Definition 1. Let F~ = hP; Q; Ri be a vector field in R3, where P , Q and R are continuously differentiable. We define the curl operator: @R @Q @P @R @Q @P curl F~ = − ~i + − ~j + − ~k: (1) @y @z @z @x @x @y Remarks: 1.