Interpolation and the Lagrange Polynomial
|
|
- Diana Nelson
- 6 years ago
- Views:
Transcription
1 Interpolation and the Lagrange Polynomial MATH 375 J. Robert Buchanan Department of Mathematics Fall 2013
2 Introduction We often choose polynomials to approximate other classes of functions. Theorem (Weierstrass Approximation Theorem) If f C[a, b] and ɛ > 0 then there exists a polynomial P such that f (x) P(x) < ɛ, for all x [a, b].
3 Introduction We often choose polynomials to approximate other classes of functions. Theorem (Weierstrass Approximation Theorem) If f C[a, b] and ɛ > 0 then there exists a polynomial P such that f (x) P(x) < ɛ, for all x [a, b]. We have used Taylor polynomials to approximate functions. n f (k) (x 0 ) P(x) = (x x 0 ) k k! k=0 Away from x 0 the approximation may be very poor.
4 Linear Approximation (1 of 2) y 1 f x 1 y 0 f x 0 x 1 x Using the two-point formula for a line we determine the equation of the line to be ( ) f (x1 ) f (x 0 ) y = f (x 0 ) + (x x 0 ). x 1 x 0
5 Linear Approximation (2 of 2) We can take another approach to finding the linear approximation. Define L 0 (x) = x x 1 x 0 x 1, L 1 (x) = x x 0 x 1 x 0,
6 Linear Approximation (2 of 2) We can take another approach to finding the linear approximation. Define L 0 (x) = x x 1 x 0 x 1, then L 0 (x 0 ) = 1 and L 0 (x 1 ) = 0. L 1 (x) = x x 0 x 1 x 0,
7 Linear Approximation (2 of 2) We can take another approach to finding the linear approximation. Define L 0 (x) = x x 1 x 0 x 1, then L 0 (x 0 ) = 1 and L 0 (x 1 ) = 0. L 1 (x) = x x 0 x 1 x 0, then L 1 (x 0 ) = 0 and L 1 (x 1 ) = 1.
8 Linear Approximation (2 of 2) We can take another approach to finding the linear approximation. Define L 0 (x) = x x 1 x 0 x 1, then L 0 (x 0 ) = 1 and L 0 (x 1 ) = 0. L 1 (x) = x x 0 x 1 x 0, then L 1 (x 0 ) = 0 and L 1 (x 1 ) = 1. If f (x) is any function then P(x) = f (x 0 ) L 0 (x) + f (x 1 ) L 1 (x) is a linear function which matches f (x) at x = x 0 and x = x 1.
9 Linear Approximation (2 of 2) We can take another approach to finding the linear approximation. Define L 0 (x) = x x 1 x 0 x 1, then L 0 (x 0 ) = 1 and L 0 (x 1 ) = 0. L 1 (x) = x x 0 x 1 x 0, then L 1 (x 0 ) = 0 and L 1 (x 1 ) = 1. If f (x) is any function then P(x) = f (x 0 ) L 0 (x) + f (x 1 ) L 1 (x) is a linear function which matches f (x) at x = x 0 and x = x 1. We want to extend this idea to higher order polynomials.
10 Construction of Polynomials Challenge: given a function f (x), construct a polynomial P(x) of degree at most n which matches f (x) at n + 1 distinct points. {(x 0, f (x 0 )), (x 1, f (x 1 )),..., (x n, f (x n ))}
11 Construction of Polynomials Challenge: given a function f (x), construct a polynomial P(x) of degree at most n which matches f (x) at n + 1 distinct points. {(x 0, f (x 0 )), (x 1, f (x 1 )),..., (x n, f (x n ))} Strategy: construct n + 1 polynomials L n,k (x) of degree n with the property that { 0 if k i, L n,k (x i ) = 1 if k = i for k = 0, 1, 2,..., n.
12 Lagrange Basis Polynomials Definition Suppose {x 0, x 1,..., x n } is a set of n + 1 distinct points. A Lagrange Basis Polynomial is a polynomial of degree n having the form L n,k (x) = n i=0, i k x x i x k x i.
13 Lagrange Basis Polynomials Definition Suppose {x 0, x 1,..., x n } is a set of n + 1 distinct points. A Lagrange Basis Polynomial is a polynomial of degree n having the form Remarks: L n,k (x) = We will let k = 0, 1, 2,..., n. L n,k (x i ) = 1 for i = k. L n,k (x i ) = 0 for i k. n i=0, i k x x i x k x i.
14 Example If x i = i for i = 0, 1, 2 then we can create three different Lagrange Basis Polynomials. L 2,0 (x) = L 2,1 (x) = L 2,2 (x) =
15 Example If x i = i for i = 0, 1, 2 then we can create three different Lagrange Basis Polynomials. L 2,0 (x) = x x = 1 (x 1)(x 2) 2 L 2,1 (x) = L 2,2 (x) =
16 Example If x i = i for i = 0, 1, 2 then we can create three different Lagrange Basis Polynomials. L 2,0 (x) = x x = 1 (x 1)(x 2) 2 L 2,1 (x) = x x 2 = x(2 x) 1 2 L 2,2 (x) =
17 Example If x i = i for i = 0, 1, 2 then we can create three different Lagrange Basis Polynomials. L 2,0 (x) = x x = 1 (x 1)(x 2) 2 L 2,1 (x) = x x 2 = x(2 x) 1 2 L 2,2 (x) = x x = 1 x(x 1) 2
18 Graph L 2,0 (x) = 1 (x 1)(x 2) 2 L 2,1 (x) = x(2 x) L 2,2 (x) = 1 2 x(x 1) x 1
19 Lagrange Interpolating Polynomials Definition Let {x 0, x 1,..., x n } be a set of n + 1 distinct points at which the function f (x) is defined. The (unique) Lagrange Interpolating Polynomial of f (x) of degree n is the polynomial having the form n P(x) = f (x k )L n,k (x). Properties: L n,k (x i ) = 0 for all i k. L n,k (x k ) = 1. k=0 P(x k ) = f (x k ) for k = 0, 1,..., n.
20 Example If n = 9 and the nodes are {0, 1,..., 9} then L 9,4 (x) has a graph resembling the following x 2 4
21 Example (1 of 3) Let f (x) = sin x, n = 3, and x k = kπ/3 for k = 0, 1, 2, 3. The four Lagrange Basis Polynomials are listed below. L 3,0 (x) = x π 3 0 π 3 x 2π 3 0 2π 3 x π 0 π = 1 (π 3x)(2π 3x)(π x) 2π3 L 3,1 (x) = 9 x(2π 3x)(π x) 2π3 L 3,2 (x) = 9 x(π 3x)(π x) 2π3 L 3,3 (x) = 1 x(π 3x)(2π 3x) 2π3
22 Example (2 of 3) The Lagrange Interpolating Polynomial of degree 3 for f (x) = sin x and x k = kπ/3 for k = 0, 1, 2, 3 is ( P(x) = (sin 0) L 3,0 (x) + sin π ) ( L 3,1 (x) + sin 2π ) L 3,2 (x) 3 3 = + (sin π) L 3,3 (x) 3 2 = 9 3 x(π x) 4π2 9 x(2π 3x)(π x) 2π x(π 3x)(π x) 2π3
23 Example (3 of 3) The graphs of P(x), f (x), and the absolute error are shown below. 1.0 Abs. Err Π x x
24 Lagrange Polynomial with Error Term Theorem Suppose x 0, x 1,..., x n are distinct numbers in the interval [a, b] and suppose f C n+1 [a, b]. Then for each x [a, b] there exists a number z(x) (a, b) for which f (x) = P(x) + f (n+1) (z(x)) (x x 0 )(x x 1 ) (x x n ), (n + 1)! where P(x) is the Lagrange Interpolating Polynomial.
25 Comments Compare the error terms of the Lagrange polynomial and the Taylor polynomial. Taylor: f (n+1) (z(x)) (x x 0 ) n+1 (n + 1)! f (n+1) (z(x)) Lagrange: (x x 0 )(x x 1 ) (x x n ) (n + 1)! Lagrange polynomials form the basis of many numerical approximations to derivatives and integrals, and thus the error term is important to understanding the errors present in those approximations.
26 Application Example Suppose we are preparing a table of values for cos x on [0, π]. The entries in the table will have eight accurate decimal places and we will linearly interpolate between adjacent entries to determine intermediate values. What should the spacing between adjacent x-values be to preserve the eight-decimal-place accuracy in the interpolation?
27 Solution cos x P(x) = cos z 2 x x j x x j+1 for some 0 z π 1 2 max 0 z π cos z max x x j x x j+1 x j x x j+1 = 1 2 = h2 8 max (x jh)(x (j + 1)h jh x (j+1)h Thus if h 2 /8 < 10 8 then h <
28 Error in sin x Earlier we found the Lagrange interpolating polynomial of degree 3 for f (x) = sin x using nodes x k = kπ/3 for k = 0, 1, 2, 3 was P(x) = 9 3 x(π x). 4π2 What is an error bound for this approximation?
29 Error in sin x Earlier we found the Lagrange interpolating polynomial of degree 3 for f (x) = sin x using nodes x k = kπ/3 for k = 0, 1, 2, 3 was P(x) = 9 3 x(π x). 4π2 What is an error bound for this approximation? R(x) = sin z ( (x 0) x π ) ( x 2π 4! 3 3 ) (x π)
30 Error Bound vs. Actual Error Π x
31 Homework Read Section 3.1 Exercises: 1, 3, 5a, 7a, 13, 17
Computer Arithmetic. MATH 375 Numerical Analysis. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Computer Arithmetic
Computer Arithmetic MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Fall 2013 Machine Numbers When performing arithmetic on a computer (laptop, desktop, mainframe, cell phone,
More informationRomberg Integration. MATH 375 Numerical Analysis. J. Robert Buchanan. Spring Department of Mathematics
Romberg Integration MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Spring 019 Objectives and Background In this lesson we will learn to obtain high accuracy approximations to
More information3.1 Interpolation and the Lagrange Polynomial
MATH 4073 Chapter 3 Interpolation and Polynomial Approximation Fall 2003 1 Consider a sample x x 0 x 1 x n y y 0 y 1 y n. Can we get a function out of discrete data above that gives a reasonable estimate
More informationCubic Splines MATH 375. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Cubic Splines
Cubic Splines MATH 375 J. Robert Buchanan Department of Mathematics Fall 2006 Introduction Given data {(x 0, f(x 0 )), (x 1, f(x 1 )),...,(x n, f(x n ))} which we wish to interpolate using a polynomial...
More informationReview of Power Series
Review of Power Series MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Introduction In addition to the techniques we have studied so far, we may use power
More informationINTERPOLATION. and y i = cos x i, i = 0, 1, 2 This gives us the three points. Now find a quadratic polynomial. p(x) = a 0 + a 1 x + a 2 x 2.
INTERPOLATION Interpolation is a process of finding a formula (often a polynomial) whose graph will pass through a given set of points (x, y). As an example, consider defining and x 0 = 0, x 1 = π/4, x
More informationNeville s Method. MATH 375 Numerical Analysis. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Neville s Method
Neville s Method MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Fall 2013 Motivation We have learned how to approximate a function using Lagrange polynomials and how to estimate
More informationLinear Independence. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics
Linear Independence MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Introduction Given a set of vectors {v 1, v 2,..., v r } and another vector v span{v 1, v 2,...,
More informationSeries Solutions Near a Regular Singular Point
Series Solutions Near a Regular Singular Point MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Background We will find a power series solution to the equation:
More informationExponential Functions
Exponential Functions MATH 160, Precalculus J. Robert Buchanan Department of Mathematics Fall 2011 Objectives In this lesson we will learn to: recognize and evaluate exponential functions with base a,
More informationAccelerating Convergence
Accelerating Convergence MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Fall 2013 Motivation We have seen that most fixed-point methods for root finding converge only linearly
More informationMean Value Theorem. MATH 161 Calculus I. J. Robert Buchanan. Summer Department of Mathematics
Mean Value Theorem MATH 161 Calculus I J. Robert Buchanan Department of Mathematics Summer 2018 Background: Corollary to the Intermediate Value Theorem Corollary Suppose f is continuous on the closed interval
More informationMean Value Theorem. MATH 161 Calculus I. J. Robert Buchanan. Summer Department of Mathematics
Mean Value Theorem MATH 161 Calculus I J. Robert Buchanan Department of Mathematics Summer 2018 Background: Corollary to the Intermediate Value Theorem Corollary Suppose f is continuous on the closed interval
More informationContinuity. MATH 161 Calculus I. J. Robert Buchanan. Fall Department of Mathematics
Continuity MATH 161 Calculus I J. Robert Buchanan Department of Mathematics Fall 2017 Intuitive Idea A process or an item can be described as continuous if it exists without interruption. The mathematical
More informationJim Lambers MAT 460/560 Fall Semester Practice Final Exam
Jim Lambers MAT 460/560 Fall Semester 2009-10 Practice Final Exam 1. Let f(x) = sin 2x + cos 2x. (a) Write down the 2nd Taylor polynomial P 2 (x) of f(x) centered around x 0 = 0. (b) Write down the corresponding
More informationNUMERICAL METHODS. x n+1 = 2x n x 2 n. In particular: which of them gives faster convergence, and why? [Work to four decimal places.
NUMERICAL METHODS 1. Rearranging the equation x 3 =.5 gives the iterative formula x n+1 = g(x n ), where g(x) = (2x 2 ) 1. (a) Starting with x = 1, compute the x n up to n = 6, and describe what is happening.
More informationAdvanced Math Quiz Review Name: Dec Use Synthetic Division to divide the first polynomial by the second polynomial.
Advanced Math Quiz 3.1-3.2 Review Name: Dec. 2014 Use Synthetic Division to divide the first polynomial by the second polynomial. 1. 5x 3 + 6x 2 8 x + 1, x 5 1. Quotient: 2. x 5 10x 3 + 5 x 1, x + 4 2.
More informationSection 8.7. Taylor and MacLaurin Series. (1) Definitions, (2) Common Maclaurin Series, (3) Taylor Polynomials, (4) Applications.
Section 8.7 Taylor and MacLaurin Series (1) Definitions, (2) Common Maclaurin Series, (3) Taylor Polynomials, (4) Applications. MATH 126 (Section 8.7) Taylor and MacLaurin Series The University of Kansas
More informationDiagonalization. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics
Diagonalization MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Motivation Today we consider two fundamental questions: Given an n n matrix A, does there exist a basis
More informationMidterm Review. Igor Yanovsky (Math 151A TA)
Midterm Review Igor Yanovsky (Math 5A TA) Root-Finding Methods Rootfinding methods are designed to find a zero of a function f, that is, to find a value of x such that f(x) =0 Bisection Method To apply
More informationApproximation theory
Approximation theory Xiaojing Ye, Math & Stat, Georgia State University Spring 2019 Numerical Analysis II Xiaojing Ye, Math & Stat, Georgia State University 1 1 1.3 6 8.8 2 3.5 7 10.1 Least 3squares 4.2
More informationINTERPOLATION Background Polynomial Approximation Problem:
INTERPOLATION Background Polynomial Approximation Problem: given f(x) C[a, b], find P n (x) = a 0 + a 1 x + a 2 x 2 + + a n x n with P n (x) close to f(x) for x [a, b]. Motivations: f(x) might be difficult
More informationLimit Theorems. MATH 464/506, Real Analysis. J. Robert Buchanan. Summer Department of Mathematics. J. Robert Buchanan Limit Theorems
Limit s MATH 464/506, Real Analysis J. Robert Buchanan Department of Mathematics Summer 2007 Bounded Functions Definition Let A R, let f : A R, and let c R be a cluster point of A. We say that f is bounded
More informationExtrema and the First-Derivative Test
Extrema and the First-Derivative Test MATH 151 Calculus for Management J. Robert Buchanan Department of Mathematics 2018 Why Maximize or Minimize? In almost all quantitative fields there are objective
More informationA first order divided difference
A first order divided difference For a given function f (x) and two distinct points x 0 and x 1, define f [x 0, x 1 ] = f (x 1) f (x 0 ) x 1 x 0 This is called the first order divided difference of f (x).
More informationInterpolation Theory
Numerical Analysis Massoud Malek Interpolation Theory The concept of interpolation is to select a function P (x) from a given class of functions in such a way that the graph of y P (x) passes through the
More informationTaylor and Maclaurin Series. Approximating functions using Polynomials.
Taylor and Maclaurin Series Approximating functions using Polynomials. Approximating f x = e x near x = 0 In order to approximate the function f x = e x near x = 0, we can use the tangent line (The Linear
More informationRow Space, Column Space, and Nullspace
Row Space, Column Space, and Nullspace MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Introduction Every matrix has associated with it three vector spaces: row space
More informationMAT137 Calculus! Lecture 45
official website http://uoft.me/mat137 MAT137 Calculus! Lecture 45 Today: Taylor Polynomials Taylor Series Next: Taylor Series Power Series Definition (Power Series) A power series is a series of the form
More informationChapter 3 Interpolation and Polynomial Approximation
Chapter 3 Interpolation and Polynomial Approximation Per-Olof Persson persson@berkeley.edu Department of Mathematics University of California, Berkeley Math 128A Numerical Analysis Polynomial Interpolation
More informationInfinite Series. MATH 211, Calculus II. J. Robert Buchanan. Spring Department of Mathematics
Infinite Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Background Consider the repeating decimal form of 2/3. 2 3 = 0.666666 = 0.6 + 0.06 + 0.006 + 0.0006 + = 6(0.1)
More information3 Interpolation and Polynomial Approximation
CHAPTER 3 Interpolation and Polynomial Approximation Introduction A census of the population of the United States is taken every 10 years. The following table lists the population, in thousands of people,
More informationTaylor and Maclaurin Series. Approximating functions using Polynomials.
Taylor and Maclaurin Series Approximating functions using Polynomials. Approximating f x = e x near x = 0 In order to approximate the function f x = e x near x = 0, we can use the tangent line (The Linear
More informationLecture Note 3: Interpolation and Polynomial Approximation. Xiaoqun Zhang Shanghai Jiao Tong University
Lecture Note 3: Interpolation and Polynomial Approximation Xiaoqun Zhang Shanghai Jiao Tong University Last updated: October 10, 2015 2 Contents 1.1 Introduction................................ 3 1.1.1
More information1 Solutions to selected problems
Solutions to selected problems Section., #a,c,d. a. p x = n for i = n : 0 p x = xp x + i end b. z = x, y = x for i = : n y = y + x i z = zy end c. y = (t x ), p t = a for i = : n y = y(t x i ) p t = p
More information1) The line has a slope of ) The line passes through (2, 11) and. 6) r(x) = x + 4. From memory match each equation with its graph.
Review Test 2 Math 1314 Name Write an equation of the line satisfying the given conditions. Write the answer in standard form. 1) The line has a slope of - 2 7 and contains the point (3, 1). Use the point-slope
More informationFixed-Point Iteration
Fixed-Point Iteration MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Fall 2013 Motivation Several root-finding algorithms operate by repeatedly evaluating a function until its
More information6.2 Deeper Properties of Continuous Functions
6.2. DEEPER PROPERTIES OF CONTINUOUS FUNCTIONS 69 6.2 Deeper Properties of Continuous Functions 6.2. Intermediate Value Theorem and Consequences When one studies a function, one is usually interested in
More informationThe Normal Equations. For A R m n with m > n, A T A is singular if and only if A is rank-deficient. 1 Proof:
Applied Math 205 Homework 1 now posted. Due 5 PM on September 26. Last time: piecewise polynomial interpolation, least-squares fitting Today: least-squares, nonlinear least-squares The Normal Equations
More informationBessel s Equation. MATH 365 Ordinary Differential Equations. J. Robert Buchanan. Fall Department of Mathematics
Bessel s Equation MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Background Bessel s equation of order ν has the form where ν is a constant. x 2 y + xy
More informationThe answer in each case is the error in evaluating the taylor series for ln(1 x) for x = which is 6.9.
Brad Nelson Math 26 Homework #2 /23/2. a MATLAB outputs: >> a=(+3.4e-6)-.e-6;a- ans = 4.449e-6 >> a=+(3.4e-6-.e-6);a- ans = 2.224e-6 And the exact answer for both operations is 2.3e-6. The reason why way
More informationMA 3021: Numerical Analysis I Numerical Differentiation and Integration
MA 3021: Numerical Analysis I Numerical Differentiation and Integration Suh-Yuh Yang ( 楊肅煜 ) Department of Mathematics, National Central University Jhongli District, Taoyuan City 32001, Taiwan syyang@math.ncu.edu.tw
More informationTaylor and Maclaurin Series
Taylor and Maclaurin Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Background We have seen that some power series converge. When they do, we can think of them as
More informationSeries Solutions Near an Ordinary Point
Series Solutions Near an Ordinary Point MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Spring 2018 Ordinary Points (1 of 2) Consider the second order linear homogeneous
More informationIntroduction Linear system Nonlinear equation Interpolation
Interpolation Interpolation is the process of estimating an intermediate value from a set of discrete or tabulated values. Suppose we have the following tabulated values: y y 0 y 1 y 2?? y 3 y 4 y 5 x
More informationInterpolating Accuracy without underlying f (x)
Example: Tabulated Data The following table x 1.0 1.3 1.6 1.9 2.2 f (x) 0.7651977 0.6200860 0.4554022 0.2818186 0.1103623 lists values of a function f at various points. The approximations to f (1.5) obtained
More information5.5 Deeper Properties of Continuous Functions
5.5. DEEPER PROPERTIES OF CONTINUOUS FUNCTIONS 195 5.5 Deeper Properties of Continuous Functions 5.5.1 Intermediate Value Theorem and Consequences When one studies a function, one is usually interested
More informationMathematics 206 Solutions for HWK 23 Section 6.3 p358
Mathematics 6 Solutions for HWK Section Problem 9. Given T(x, y, z) = (x 9y + z,6x + 5y z) and v = (,,), use the standard matrix for the linear transformation T to find the image of the vector v. Note
More informationDownloaded from
Question 1: Exercise 2.1 The graphs of y = p(x) are given in following figure, for some polynomials p(x). Find the number of zeroes of p(x), in each case. (i) (ii) (iii) Page 1 of 24 (iv) (v) (v) Page
More informationFunctions: Polynomial, Rational, Exponential
Functions: Polynomial, Rational, Exponential MATH 151 Calculus for Management J. Robert Buchanan Department of Mathematics Spring 2014 Objectives In this lesson we will learn to: identify polynomial expressions,
More informationReview all the activities leading to Midterm 3. Review all the problems in the previous online homework sets (8+9+10).
MA109, Activity 34: Review (Sections 3.6+3.7+4.1+4.2+4.3) Date: Objective: Additional Assignments: To prepare for Midterm 3, make sure that you can solve the types of problems listed in Activities 33 and
More informationInterpolation and Approximation
Interpolation and Approximation The Basic Problem: Approximate a continuous function f(x), by a polynomial p(x), over [a, b]. f(x) may only be known in tabular form. f(x) may be expensive to compute. Definition:
More information2.3 Some Properties of Continuous Functions
2.3 Some Properties of Continuous Functions In this section we look at some properties, some quite deep, shared by all continuous functions. They are known as the following: 1. Preservation of sign property
More information1 Solutions to selected problems
Solutions to selected problems Section., #a,c,d. a. p x = n for i = n : 0 p x = xp x + i end b. z = x, y = x for i = : n y = y + x i z = zy end c. y = (t x ), p t = a for i = : n y = y(t x i ) p t = p
More informationMATH 1014 Tutorial Notes 8
MATH4 Calculus II (8 Spring) Topics covered in tutorial 8:. Numerical integration. Approximation integration What you need to know: Midpoint rule & its error Trapezoid rule & its error Simpson s rule &
More informationCalculus and Parametric Equations
Calculus and Parametric Equations MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Introduction Given a pair a parametric equations x = f (t) y = g(t) for a t b we know how
More informationMath 601 Solutions to Homework 3
Math 601 Solutions to Homework 3 1 Use Cramer s Rule to solve the following system of linear equations (Solve for x 1, x 2, and x 3 in terms of a, b, and c 2x 1 x 2 + 7x 3 = a 5x 1 2x 2 x 3 = b 3x 1 x
More informationMath 334 A1 Homework 3 (Due Nov. 5 5pm)
Math 334 A1 Homework 3 Due Nov. 5 5pm No Advanced or Challenge problems will appear in homeworks. Basic Problems Problem 1. 4.1 11 Verify that the given functions are solutions of the differential equation,
More informationNumerical Methods of Approximation
Contents 31 Numerical Methods of Approximation 31.1 Polynomial Approximations 2 31.2 Numerical Integration 28 31.3 Numerical Differentiation 58 31.4 Nonlinear Equations 67 Learning outcomes In this Workbook
More informationHomework #6 Solutions
Problems Section.1: 6, 4, 40, 46 Section.:, 8, 10, 14, 18, 4, 0 Homework #6 Solutions.1.6. Determine whether the functions f (x) = cos x + sin x and g(x) = cos x sin x are linearly dependent or linearly
More informationExtrema of Functions of Several Variables
Extrema of Functions of Several Variables MATH 311, Calculus III J. Robert Buchanan Department of Mathematics Fall 2011 Background (1 of 3) In single-variable calculus there are three important results
More informationMEMORIAL UNIVERSITY OF NEWFOUNDLAND
MEMORIAL UNIVERSITY OF NEWFOUNDLAND DEPARTMENT OF MATHEMATICS AND STATISTICS Section 5. Math 090 Fall 009 SOLUTIONS. a) Using long division of polynomials, we have x + x x x + ) x 4 4x + x + 0x x 4 6x
More information8.2 Discrete Least Squares Approximation
Chapter 8 Approximation Theory 8.1 Introduction Approximation theory involves two types of problems. One arises when a function is given explicitly, but we wish to find a simpler type of function, such
More information1 Lecture 8: Interpolating polynomials.
1 Lecture 8: Interpolating polynomials. 1.1 Horner s method Before turning to the main idea of this part of the course, we consider how to evaluate a polynomial. Recall that a polynomial is an expression
More informationLagrange s polynomial
Lagrange s polynomial Nguyen Trung Tuan November 13, 2016 Abstract...In numerical analysis, Lagrange polynomials are used for polynomial interpolation. For a given set of distinct points x j and numbers
More informationNumerical Methods. King Saud University
Numerical Methods King Saud University Aims In this lecture, we will... find the approximate solutions of derivative (first- and second-order) and antiderivative (definite integral only). Numerical Differentiation
More informationInverses. Stephen Boyd. EE103 Stanford University. October 28, 2017
Inverses Stephen Boyd EE103 Stanford University October 28, 2017 Outline Left and right inverses Inverse Solving linear equations Examples Pseudo-inverse Left and right inverses 2 Left inverses a number
More informationFundamental Theorem of Calculus
Fundamental Theorem of Calculus MATH 6 Calculus I J. Robert Buchanan Department of Mathematics Summer 208 Remarks The Fundamental Theorem of Calculus (FTC) will make the evaluation of definite integrals
More informationSecondary Math 3 Honors - Polynomial and Polynomial Functions Test Review
Name: Class: Date: Secondary Math 3 Honors - Polynomial and Polynomial Functions Test Review 1 Write 3x 2 ( 2x 2 5x 3 ) in standard form State whether the function is even, odd, or neither Show your work
More informationChapter 4: Interpolation and Approximation. October 28, 2005
Chapter 4: Interpolation and Approximation October 28, 2005 Outline 1 2.4 Linear Interpolation 2 4.1 Lagrange Interpolation 3 4.2 Newton Interpolation and Divided Differences 4 4.3 Interpolation Error
More informationLIMITS AT INFINITY MR. VELAZQUEZ AP CALCULUS
LIMITS AT INFINITY MR. VELAZQUEZ AP CALCULUS RECALL: VERTICAL ASYMPTOTES Remember that for a rational function, vertical asymptotes occur at values of x = a which have infinite its (either positive or
More information' Liberty and Umou Ono and Inseparablo "
3 5? #< q 8 2 / / ) 9 ) 2 ) > < _ / ] > ) 2 ) ) 5 > x > [ < > < ) > _ ] ]? <
More informationChain Rule. MATH 311, Calculus III. J. Robert Buchanan. Spring Department of Mathematics
3.33pt Chain Rule MATH 311, Calculus III J. Robert Buchanan Department of Mathematics Spring 2019 Single Variable Chain Rule Suppose y = g(x) and z = f (y) then dz dx = d (f (g(x))) dx = f (g(x))g (x)
More informationCompletion Date: Monday February 11, 2008
MATH 4 (R) Winter 8 Intermediate Calculus I Solutions to Problem Set #4 Completion Date: Monday February, 8 Department of Mathematical and Statistical Sciences University of Alberta Question. [Sec..9,
More informationEvaluating Determinants by Row Reduction
Evaluating Determinants by Row Reduction MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Objectives Reduce a matrix to row echelon form and evaluate its determinant.
More informationLecture Note 3: Polynomial Interpolation. Xiaoqun Zhang Shanghai Jiao Tong University
Lecture Note 3: Polynomial Interpolation Xiaoqun Zhang Shanghai Jiao Tong University Last updated: October 24, 2013 1.1 Introduction We first look at some examples. Lookup table for f(x) = 2 π x 0 e x2
More informationSkills Practice Skills Practice for Lesson 10.1
Skills Practice Skills Practice for Lesson.1 Name Date Higher Order Polynomials and Factoring Roots of Polynomial Equations Problem Set Solve each polynomial equation using factoring. Then check your solution(s).
More informationTwo hours. To be provided by Examinations Office: Mathematical Formula Tables. THE UNIVERSITY OF MANCHESTER. 29 May :45 11:45
Two hours MATH20602 To be provided by Examinations Office: Mathematical Formula Tables. THE UNIVERSITY OF MANCHESTER NUMERICAL ANALYSIS 1 29 May 2015 9:45 11:45 Answer THREE of the FOUR questions. If more
More informationMATH ASSIGNMENT 07 SOLUTIONS. 8.1 Following is census data showing the population of the US between 1900 and 2000:
MATH4414.01 ASSIGNMENT 07 SOLUTIONS 8.1 Following is census data showing the population of the US between 1900 and 2000: Years after 1900 Population in millions 0 76.0 20 105.7 40 131.7 60 179.3 80 226.5
More informationMA2501 Numerical Methods Spring 2015
Norwegian University of Science and Technology Department of Mathematics MA5 Numerical Methods Spring 5 Solutions to exercise set 9 Find approximate values of the following integrals using the adaptive
More informationPRACTICE PROBLEM SET
PRACTICE PROBLEM SET NOTE: On the exam, you will have to show all your work (unless told otherwise), so write down all your steps and justify them. Exercise. Solve the following inequalities: () x < 3
More informationBSM510 Numerical Analysis
BSM510 Numerical Analysis Polynomial Interpolation Prof. Manar Mohaisen Department of EEC Engineering Review of Precedent Lecture Polynomial Regression Multiple Linear Regression Nonlinear Regression Lecture
More informationSection 10.7 Taylor series
Section 10.7 Taylor series 1. Common Maclaurin series 2. s and approximations with Taylor polynomials 3. Multiplication and division of power series Math 126 Enhanced 10.7 Taylor Series The University
More informationAP Calculus (BC) Chapter 9 Test No Calculator Section Name: Date: Period:
WORKSHEET: Series, Taylor Series AP Calculus (BC) Chapter 9 Test No Calculator Section Name: Date: Period: 1 Part I. Multiple-Choice Questions (5 points each; please circle the correct answer.) 1. The
More informationNumerical Mathematics & Computing, 7 Ed. 4.1 Interpolation
Numerical Mathematics & Computing, 7 Ed. 4.1 Interpolation Ward Cheney/David Kincaid c UT Austin Engage Learning: Thomson-Brooks/Cole www.engage.com www.ma.utexas.edu/cna/nmc6 November 7, 2011 2011 1 /
More informationCHAPTER 2 POLYNOMIALS KEY POINTS
CHAPTER POLYNOMIALS KEY POINTS 1. Polynomials of degrees 1, and 3 are called linear, quadratic and cubic polynomials respectively.. A quadratic polynomial in x with real coefficient is of the form a x
More informationSolutions 2. January 23, x x
Solutions 2 January 23, 2016 1 Exercise 3.1.1 (a), p. 149 Let us compute Lagrange polynomials first for our case x 1 = 0, x 2 = 2, x 3 = 3: In [14]: from sympy import * init_printing(use_latex=true) x=symbols(
More informationLagrange s polynomial
Lagrange s polynomial Nguyen Trung Tuan November 16, 2016 Abstract In this article, I will use Lagrange polynomial to solve some problems from Mathematical Olympiads. Contents 1 Lagrange s interpolation
More informationExam 2. Average: 85.6 Median: 87.0 Maximum: Minimum: 55.0 Standard Deviation: Numerical Methods Fall 2011 Lecture 20
Exam 2 Average: 85.6 Median: 87.0 Maximum: 100.0 Minimum: 55.0 Standard Deviation: 10.42 Fall 2011 1 Today s class Multiple Variable Linear Regression Polynomial Interpolation Lagrange Interpolation Newton
More informationReview 1 Math 321: Linear Algebra Spring 2010
Department of Mathematics and Statistics University of New Mexico Review 1 Math 321: Linear Algebra Spring 2010 This is a review for Midterm 1 that will be on Thursday March 11th, 2010. The main topics
More informationProperties of Linear Transformations from R n to R m
Properties of Linear Transformations from R n to R m MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Topic Overview Relationship between the properties of a matrix transformation
More informationWe consider the problem of finding a polynomial that interpolates a given set of values:
Chapter 5 Interpolation 5. Polynomial Interpolation We consider the problem of finding a polynomial that interpolates a given set of values: x x 0 x... x n y y 0 y... y n where the x i are all distinct.
More informationVectors in the Plane
Vectors in the Plane MATH 311, Calculus III J. Robert Buchanan Department of Mathematics Fall 2011 Vectors vs. Scalars scalar quantity having only a magnitude (e.g. temperature, volume, length, area) and
More informationLecture 10 Polynomial interpolation
Lecture 10 Polynomial interpolation Weinan E 1,2 and Tiejun Li 2 1 Department of Mathematics, Princeton University, weinan@princeton.edu 2 School of Mathematical Sciences, Peking University, tieli@pku.edu.cn
More informationLimits and Continuity
Limits and Continuity MATH 151 Calculus for Management J. Robert Buchanan Department of Mathematics Fall 2018 Objectives After this lesson we will be able to: Determine the left-hand and right-hand limits
More information6.1 Polynomial Functions
6.1 Polynomial Functions Definition. A polynomial function is any function p(x) of the form p(x) = p n x n + p n 1 x n 1 + + p 2 x 2 + p 1 x + p 0 where all of the exponents are non-negative integers and
More information. Get closed expressions for the following subsequences and decide if they converge. (1) a n+1 = (2) a 2n = (3) a 2n+1 = (4) a n 2 = (5) b n+1 =
Math 316, Intro to Analysis subsequences. Recall one of our arguments about why a n = ( 1) n diverges. Consider the subsequences a n = ( 1) n = +1. It converges to 1. On the other hand, the subsequences
More informationQuestion 1: The graphs of y = p(x) are given in following figure, for some Polynomials p(x). Find the number of zeroes of p(x), in each case.
Class X - NCERT Maths EXERCISE NO:.1 Question 1: The graphs of y = p(x) are given in following figure, for some Polynomials p(x). Find the number of zeroes of p(x), in each case. (i) (ii) (iii) (iv) (v)
More informationAP Calculus Testbank (Chapter 9) (Mr. Surowski)
AP Calculus Testbank (Chapter 9) (Mr. Surowski) Part I. Multiple-Choice Questions n 1 1. The series will converge, provided that n 1+p + n + 1 (A) p > 1 (B) p > 2 (C) p >.5 (D) p 0 2. The series
More informationa. Do you think the function is linear or non-linear? Explain using what you know about powers of variables.
8.5.8 Lesson Date: Graphs of Non-Linear Functions Student Objectives I can examine the average rate of change for non-linear functions and learn that they do not have a constant rate of change. I can determine
More information