Topics in Number Theory, Algebra, and Geometry
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Fast and Efficient Algorithms for Evaluating Uniform and Nonuniform
World Academy of Science, Engineering and Technology International Journal of Computer and Information Engineering Vol:13, No:8, 2019 Fast and Efficient Algorithms for Evaluating Uniform and Nonuniform Lagrange and Newton Curves Taweechai Nuntawisuttiwong, Natasha Dejdumrong Abstract—Newton-Lagrange Interpolations are widely used in quadratic computation time, which is slower than the others. numerical analysis. However, it requires a quadratic computational However, there are some curves in CAGD, Wang-Ball, DP time for their constructions. In computer aided geometric design and Dejdumrong curves with linear complexity. In order to (CAGD), there are some polynomial curves: Wang-Ball, DP and Dejdumrong curves, which have linear time complexity algorithms. reduce their computational time, Bezier´ curve is converted Thus, the computational time for Newton-Lagrange Interpolations into any of Wang-Ball, DP and Dejdumrong curves. Hence, can be reduced by applying the algorithms of Wang-Ball, DP and the computational time for Newton-Lagrange interpolations Dejdumrong curves. In order to use Wang-Ball, DP and Dejdumrong can be reduced by converting them into Wang-Ball, DP and algorithms, first, it is necessary to convert Newton-Lagrange Dejdumrong algorithms. Thus, it is necessary to investigate polynomials into Wang-Ball, DP or Dejdumrong polynomials. In this work, the algorithms for converting from both uniform and the conversion from Newton-Lagrange interpolation into non-uniform Newton-Lagrange polynomials into Wang-Ball, DP and the curves with linear complexity, Wang-Ball, DP and Dejdumrong polynomials are investigated. Thus, the computational Dejdumrong curves. An application of this work is to modify time for representing Newton-Lagrange polynomials can be reduced sketched image in CAD application with the computational into linear complexity. -
Mials P
Euclid's Algorithm 171 Euclid's Algorithm Horner’s method is a special case of Euclid's Algorithm which constructs, for given polyno- mials p and h =6 0, (unique) polynomials q and r with deg r<deg h so that p = hq + r: For variety, here is a nonstandard discussion of this algorithm, in terms of elimination. Assume that d h(t)=a0 + a1t + ···+ adt ;ad =06 ; and n p(t)=b0 + b1t + ···+ bnt : Then we seek a polynomial n−d q(t)=c0 + c1t + ···+ cn−dt for which r := p − hq has degree <d. This amounts to the square upper triangular linear system adc0 + ad−1c1 + ···+ a0cd = bd adc1 + ad−1c2 + ···+ a0cd+1 = bd+1 . adcn−d−1 + ad−1cn−d = bn−1 adcn−d = bn for the unknown coefficients c0;:::;cn−d which can be uniquely solved by back substitution since its diagonal entries all equal ad =0.6 19aug02 c 2002 Carl de Boor 172 18. Index Rough index for these notes 1-1:-5,2,8,40 cartesian product: 2 1-norm: 79 Cauchy(-Bunyakovski-Schwarz) 2-norm: 79 Inequality: 69 A-invariance: 125 Cauchy-Binet formula: -9, 166 A-invariant: 113 Cayley-Hamilton Theorem: 133 absolute value: 167 CBS Inequality: 69 absolutely homogeneous: 70, 79 Chaikin algorithm: 139 additive: 20 chain rule: 153 adjugate: 164 change of basis: -6 affine: 151 characteristic function: 7 affine combination: 148, 150 characteristic polynomial: -8, 130, 132, 134 affine hull: 150 circulant: 140 affine map: 149 codimension: 50, 53 affine polynomial: 152 coefficient vector: 21 affine space: 149 cofactor: 163 affinely independent: 151 column map: -6, 23 agrees with y at Λt:59 column space: 29 algebraic dual: 95 column -
CS321-001 Introduction to Numerical Methods
CS321-001 Introduction to Numerical Methods Lecture 3 Interpolation and Numerical Differentiation Professor Jun Zhang Department of Computer Science University of Kentucky Lexington, KY 40506-0633 Polynomial Interpolation Given a set of discrete values, how can we estimate other values between these data The method that we will use is called polynomial interpolation. We assume the data we had are from the evaluation of a smooth function. We may be able to use a polynomial p(x) to approximate this function, at least locally. A condition: the polynomial p(x) takes the given values at the given points (nodes), i.e., p(xi) = yi with 0 ≤ i ≤ n. The polynomial is said to interpolate the table, since we do not know the function. 2 Polynomial Interpolation Note that all the points are passed through by the curve 3 Polynomial Interpolation We do not know the original function, the interpolation may not be accurate 4 Order of Interpolating Polynomial A polynomial of degree 0, a constant function, interpolates one set of data If we have two sets of data, we can have an interpolating polynomial of degree 1, a linear function x x1 x x0 p(x) y0 y1 x0 x1 x1 x0 y1 y0 y0 (x x0 ) x1 x0 Review carefully if the interpolation condition is satisfied Interpolating polynomials can be written in several forms, the most well known ones are the Lagrange form and Newton form. Each has some advantages 5 Lagrange Form For a set of fixed nodes x0, x1, …, xn, the cardinal functions, l0, l1,…, ln, are defined as 0 if i j li (x j ) ij -
Survey of Modern Mathematical Topics Inspired by History of Mathematics
Survey of Modern Mathematical Topics inspired by History of Mathematics Paul L. Bailey Department of Mathematics, Southern Arkansas University E-mail address: [email protected] Date: January 21, 2009 i Contents Preface vii Chapter I. Bases 1 1. Introduction 1 2. Integer Expansion Algorithm 2 3. Radix Expansion Algorithm 3 4. Rational Expansion Property 4 5. Regular Numbers 5 6. Problems 6 Chapter II. Constructibility 7 1. Construction with Straight-Edge and Compass 7 2. Construction of Points in a Plane 7 3. Standard Constructions 8 4. Transference of Distance 9 5. The Three Greek Problems 9 6. Construction of Squares 9 7. Construction of Angles 10 8. Construction of Points in Space 10 9. Construction of Real Numbers 11 10. Hippocrates Quadrature of the Lune 14 11. Construction of Regular Polygons 16 12. Problems 18 Chapter III. The Golden Section 19 1. The Golden Section 19 2. Recreational Appearances of the Golden Ratio 20 3. Construction of the Golden Section 21 4. The Golden Rectangle 21 5. The Golden Triangle 22 6. Construction of a Regular Pentagon 23 7. The Golden Pentagram 24 8. Incommensurability 25 9. Regular Solids 26 10. Construction of the Regular Solids 27 11. Problems 29 Chapter IV. The Euclidean Algorithm 31 1. Induction and the Well-Ordering Principle 31 2. Division Algorithm 32 iii iv CONTENTS 3. Euclidean Algorithm 33 4. Fundamental Theorem of Arithmetic 35 5. Infinitude of Primes 36 6. Problems 36 Chapter V. Archimedes on Circles and Spheres 37 1. Precursors of Archimedes 37 2. Results from Euclid 38 3. Measurement of a Circle 39 4. -
Math 3010 § 1. Treibergs First Midterm Exam Name
Math 3010 x 1. First Midterm Exam Name: Solutions Treibergs February 7, 2018 1. For each location, fill in the corresponding map letter. For each mathematician, fill in their principal location by number, and dates and mathematical contribution by letter. Mathematician Location Dates Contribution Archimedes 5 e β Euclid 1 d δ Plato 2 c ζ Pythagoras 3 b γ Thales 4 a α Locations Dates Contributions 1. Alexandria E a. 624{547 bc α. Advocated the deductive method. First man to have a theorem attributed to him. 2. Athens D b. 580{497 bc β. Discovered theorems using mechanical intuition for which he later provided rigorous proofs. 3. Croton A c. 427{346 bc γ. Explained musical harmony in terms of whole number ratios. Found that some lengths are irrational. 4. Miletus D d. 330{270 bc δ. His books set the standard for mathematical rigor until the 19th century. 5. Syracuse B e. 287{212 bc ζ. Theorems require sound definitions and proofs. The line and the circle are the purest elements of geometry. 1 2. Use the Euclidean algorithm to find the greatest common divisor of 168 and 198. Find two integers x and y so that gcd(198; 168) = 198x + 168y: Give another example of a Diophantine equation. What property does it have to be called Diophantine? (Saying that it was invented by Diophantus gets zero points!) 198 = 1 · 168 + 30 168 = 5 · 30 + 18 30 = 1 · 18 + 12 18 = 1 · 12 + 6 12 = 3 · 6 + 0 So gcd(198; 168) = 6. 6 = 18 − 12 = 18 − (30 − 18) = 2 · 18 − 30 = 2 · (168 − 5 · 30) − 30 = 2 · 168 − 11 · 30 = 2 · 168 − 11 · (198 − 168) = 13 · 168 − 11 · 198 Thus x = −11 and y = 13 . -
Lagrange & Newton Interpolation
Lagrange & Newton interpolation In this section, we shall study the polynomial interpolation in the form of Lagrange and Newton. Given a se- quence of (n +1) data points and a function f, the aim is to determine an n-th degree polynomial which interpol- ates f at these points. We shall resort to the notion of divided differences. Interpolation Given (n+1) points {(x0, y0), (x1, y1), …, (xn, yn)}, the points defined by (xi)0≤i≤n are called points of interpolation. The points defined by (yi)0≤i≤n are the values of interpolation. To interpolate a function f, the values of interpolation are defined as follows: yi = f(xi), i = 0, …, n. Lagrange interpolation polynomial The purpose here is to determine the unique polynomial of degree n, Pn which verifies Pn(xi) = f(xi), i = 0, …, n. The polynomial which meets this equality is Lagrange interpolation polynomial n Pnx=∑ l j x f x j j=0 where the lj ’s are polynomials of degree n forming a basis of Pn n x−xi x−x0 x−x j−1 x−x j 1 x−xn l j x= ∏ = ⋯ ⋯ i=0,i≠ j x j −xi x j−x0 x j−x j−1 x j−x j1 x j−xn Properties of Lagrange interpolation polynomial and Lagrange basis They are the lj polynomials which verify the following property: l x = = 1 i= j , ∀ i=0,...,n. j i ji {0 i≠ j They form a basis of the vector space Pn of polynomials of degree at most equal to n n ∑ j l j x=0 j=0 By setting: x = xi, we obtain: n n ∑ j l j xi =∑ j ji=0 ⇒ i =0 j=0 j=0 The set (lj)0≤j≤n is linearly independent and consists of n + 1 vectors. -
Mathematical Topics
A Mathematical Topics This chapter discusses most of the mathematical background needed for a thor ough understanding of the material presented in the book. It has been mentioned in the Preface, however, that math concepts which are only used once (such as the mediation operator and points vs. vectors) are discussed right where they are introduced. Do not worry too much about your difficulties in mathematics, I can assure you that mine a.re still greater. - Albert Einstein. A.I Fourier Transforms Our curves are functions of an arbitrary parameter t. For functions used in science and engineering, time is often the parameter (or the independent variable). We, therefore, say that a function g( t) is represented in the time domain. Since a typical function oscillates, we can think of it as being similar to a wave and we may try to represent it as a wave (or as a combination of waves). When this is done, we have the function G(f), where f stands for the frequency of the wave, and we say that the function is represented in the frequency domain. This turns out to be a useful concept, since many operations on functions are easy to carry out in the frequency domain. Transforming a function between the time and frequency domains is easy when the function is periodic, but it can also be done for certain non periodic functions. The present discussion is restricted to periodic functions. 1IIIt Definition: A function g( t) is periodic if (and only if) there exists a constant P such that g(t+P) = g(t) for all values of t (Figure A.la). -
CSU200 Discrete Structures Professor Fell Integers and Division
CSU200 Discrete Structures Professor Fell Integers and Division Though you probably learned about integers and division back in fourth grade, we need formal definitions and theorems to describe the algorithms we use and to very that they are correct, in general. If a and b are integers, a ¹ 0, we say a divides b if there is an integer c such that b = ac. a is a factor of b. a | b means a divides b. a | b mean a does not divide b. Theorem 1: Let a, b, and c be integers, then 1. if a | b and a | c then a | (b + c) 2. if a | b then a | bc for all integers, c 3. if a | b and b | c then a | c. Proof: Here is a proof of 1. Try to prove the others yourself. Assume a, b, and c be integers and that a | b and a | c. From the definition of divides, there must be integers m and n such that: b = ma and c = na. Then, adding equals to equals, we have b + c = ma + na. By the distributive law and commutativity, b + c = (m + n)a. By closure of addition, m + n is an integer so, by the definition of divides, a | (b + c). Q.E.D. Corollary: If a, b, and c are integers such that a | b and a | c then a | (mb + nc) for all integers m and n. Primes A positive integer p > 1 is called prime if the only positive factor of p are 1 and p. -
History of Mathematics Log of a Course
History of mathematics Log of a course David Pierce / This work is licensed under the Creative Commons Attribution–Noncommercial–Share-Alike License. To view a copy of this license, visit http://creativecommons.org/licenses/by-nc-sa/3.0/ CC BY: David Pierce $\ C Mathematics Department Middle East Technical University Ankara Turkey http://metu.edu.tr/~dpierce/ [email protected] Contents Prolegomena Whatishere .................................. Apology..................................... Possibilitiesforthefuture . I. Fall semester . Euclid .. Sunday,October ............................ .. Thursday,October ........................... .. Friday,October ............................. .. Saturday,October . .. Tuesday,October ........................... .. Friday,October ............................ .. Thursday,October. .. Saturday,October . .. Wednesday,October. ..Friday,November . ..Friday,November . ..Wednesday,November. ..Friday,November . ..Friday,November . ..Saturday,November. ..Friday,December . ..Tuesday,December . . Apollonius and Archimedes .. Tuesday,December . .. Saturday,December . .. Friday,January ............................. .. Friday,January ............................. Contents II. Spring semester Aboutthecourse ................................ . Al-Khw¯arizm¯ı, Th¯abitibnQurra,OmarKhayyám .. Thursday,February . .. Tuesday,February. .. Thursday,February . .. Tuesday,March ............................. . Cardano .. Thursday,March ............................ .. Excursus................................. -
A Low‐Cost Solution to Motion Tracking Using an Array of Sonar Sensors and An
A Low‐cost Solution to Motion Tracking Using an Array of Sonar Sensors and an Inertial Measurement Unit A thesis presented to the faculty of the Russ College of Engineering and Technology of Ohio University In partial fulfillment of the requirements for the degree Master of Science Jason S. Maxwell August 2009 © 2009 Jason S. Maxwell. All Rights Reserved. 2 This thesis titled A Low‐cost Solution to Motion Tracking Using an Array of Sonar Sensors and an Inertial Measurement Unit by JASON S. MAXWELL has been approved for the School of Electrical Engineering Computer Science and the Russ College of Engineering and Technology by Maarten Uijt de Haag Associate Professor School of Electrical Engineering and Computer Science Dennis Irwin Dean, Russ College of Engineering and Technology 3 ABSTRACT MAXWELL, JASON S., M.S., August 2009, Electrical Engineering A Low‐cost Solution to Motion Tracking Using an Array of Sonar Sensors and an Inertial Measurement Unit (91 pp.) Director of Thesis: Maarten Uijt de Haag As the desire and need for unmanned aerial vehicles (UAV) increases, so to do the navigation and system demands for the vehicles. While there are a multitude of systems currently offering solutions, each also possess inherent problems. The Global Positioning System (GPS), for instance, is potentially unable to meet the demands of vehicles that operate indoors, in heavy foliage, or in urban canyons, due to the lack of signal strength. Laser‐based systems have proven to be rather costly, and can potentially fail in areas in which the surface absorbs light, and in urban environments with glass or mirrored surfaces. -
The AMATYC Review, Fall 1992-Spring 1993. INSTITUTION American Mathematical Association of Two-Year Colleges
DOCUMENT RESUME ED 354 956 JC 930 126 AUTHOR Cohen, Don, Ed.; Browne, Joseph, Ed. TITLE The AMATYC Review, Fall 1992-Spring 1993. INSTITUTION American Mathematical Association of Two-Year Colleges. REPORT NO ISSN-0740-8404 PUB DATE 93 NOTE 203p. AVAILABLE FROMAMATYC Treasurer, State Technical Institute at Memphis, 5983 Macon Cove, Memphis, TN 38134 (for libraries 2 issues free with $25 annual membership). PUB TYPE Collected Works Serials (022) JOURNAL CIT AMATYC Review; v14 n1-2 Fall 1992-Spr 1993 EDRS PRICE MF01/PC09 Plus Postage. DESCRIPTORS *College Mathematics; Community Colleges; Computer Simulation; Functions (Mathematics); Linear Programing; *Mathematical Applications; *Mathematical Concepts; Mathematical Formulas; *Mathematics Instruction; Mathematics Teachers; Technical Mathematics; Two Year Colleges ABSTRACT Designed as an avenue of communication for mathematics educators concerned with the views, ideas, and experiences of two-year collage students and teachers, this journal contains articles on mathematics expoition and education,as well as regular features presenting book and software reviews and math problems. The first of two issues of volume 14 contains the following major articles: "Technology in the Mathematics Classroom," by Mike Davidson; "Reflections on Arithmetic-Progression Factorials," by William E. Rosentl,e1; "The Investigation of Tangent Polynomials with a Computer Algebra System," by John H. Mathews and Russell W. Howell; "On Finding the General Term of a Sequence Using Lagrange Interpolation," by Sheldon Gordon and Robert Decker; "The Floating Leaf Problem," by Richard L. Francis; "Approximations to the Hypergeometric Distribution," by Chltra Gunawardena and K. L. D. Gunawardena; aid "Generating 'JE(3)' with Some Elementary Applications," by John J. Edgeli, Jr. The second issue contains: "Strategies for Making Mathematics Work for Minorities," by Beverly J. -
Discrete Mathematics Homework 3
Discrete Mathematics Homework 3 Ethan Bolker November 15, 2014 Due: ??? We're studying number theory (leading up to cryptography) for the next few weeks. You can read Unit NT in Bender and Williamson. This homework contains some programming exercises, some number theory computations and some proofs. The questions aren't arranged in any particular order. Don't just start at the beginning and do as many as you can { read them all and do the easy ones first. I may add to this homework from time to time. Exercises 1. Use the Euclidean algorithm to compute the greatest common divisor d of 59400 and 16200 and find integers x and y such that 59400x + 16200y = d I recommend that you do this by hand for the logical flow (a calculator is fine for the arith- metic) before writing the computer programs that follow. There are many websites that will do the computation for you, and even show you the steps. If you use one, tell me which one. We wish to find gcd(16200; 59400). Solution LATEX note. These are separate equations in the source file. They'd be better formatted in an align* environment. 59400 = 3(16200) + 10800 next find gcd(10800; 16200) 16200 = 1(10800) + 5400 next find gcd(5400; 10800) 10800 = 2(5400) + 0 gcd(16200; 59400) = 5400 59400x + 16200y = 5400 5400(11x + 3y) = 5400 11x + 3y = 1 By inspection, we can easily determine that (x; y) = (−1; 4) (among other solutions), but let's use the algorithm. 11 = 3 · 3 + 2 3 = 2 · 1 + 1 1 = 3 − (2) · 1 1 = 3 − (11 − 3 · 3) 1 = 11(−1) + 3(4) (x; y) = (−1; 4) 1 2.