Multiple-Choice Test Spline Method Interpolation COMPLETE SOLUTION SET

Similar documents
ES 240: Scientific and Engineering Computation. a function f(x) that can be written as a finite series of power functions like

ME 261: Numerical Analysis Lecture-12: Numerical Interpolation

5.1 Introduction to the Graphs of Polynomials

Handout 4 - Interpolation Examples

Computational Physics PHYS 420

Curve fitting using linear models

Test 3 review SHORT ANSWER. Write the word or phrase that best completes each statement or answers the question.

Mar. 20 Math 2335 sec 001 Spring 2014

Interpolation - 2D mapping Tutorial 1: triangulation

Lecture 6: Interpolation

Lecture 8. Divided Differences,Least-Squares Approximations. Ceng375 Numerical Computations at December 9, 2010

UNIT #2 TRANSFORMATIONS OF FUNCTIONS

Core Mathematics 1 Graphs of Functions

Parameterization. Michael S. Floater. November 10, 2011

Kevin James. MTHSC 102 Section 1.5 Polynomial Functions and Models

Skill Sets Chapter 5 Functions

Friday, 11 January 13. Interpolation

The Interpolating Polynomial

Interpolation & Polynomial Approximation. Cubic Spline Interpolation II

Computer Graphics / Animation

Algebra 1 Semester 2 Final Review

lecture 10: B-Splines

Numerical Methods in Physics Lecture 2 Interpolation

MATH 1101 Exam 4 Review. Spring 2018

Piecewise polynomial interpolation

QUADRATIC AND CUBIC GRAPHS

Cubic spline interpolation

CURVE SKETCHING EXAM QUESTIONS

Supplemental 1.5. Objectives Interval Notation Increasing & Decreasing Functions Average Rate of Change Difference Quotient

Interactive Graphics. Lecture 9: Introduction to Spline Curves. Interactive Graphics Lecture 9: Slide 1

Section 3.3. Analyzing Graphs of Quadratic Functions

9.8 Graphing Rational Functions

Chapter 12: Quadratic and Cubic Graphs

Today is the last day to register for CU Succeed account AND claim your account. Tuesday is the last day to register for my class

Linear, Quadratic, Exponential, and Absolute Value Functions

Consider functions such that then satisfies these properties: So is represented by the cubic polynomials on on and on.

2.4. A LIBRARY OF PARENT FUNCTIONS

Generalised Mean Averaging Interpolation by Discrete Cubic Splines

15.10 Curve Interpolation using Uniform Cubic B-Spline Curves. CS Dept, UK

EECS 556 Image Processing W 09. Interpolation. Interpolation techniques B splines

Polynomial Graph Features: 1. Must be a smooth continuous curve (no holes, or sharp corners) Graphing Polynomial Functions

UNIT 3 EXPRESSIONS AND EQUATIONS Lesson 3: Creating Quadratic Equations in Two or More Variables

CS-184: Computer Graphics

Rational Bezier Curves

Smoothing and Forecasting Mortality Rates with P-splines. Iain Currie. Data and problem. Plan of talk

APPM/MATH Problem Set 4 Solutions

Video 11.1 Vijay Kumar. Property of University of Pennsylvania, Vijay Kumar

Core Mathematics 1 Transformations of Graphs

f( x ), or a solution to the equation f( x) 0. You are already familiar with ways of solving

February 2017 (1/20) 2 Piecewise Polynomial Interpolation 2.2 (Natural) Cubic Splines. MA378/531 Numerical Analysis II ( NA2 )

ALGEBRA 2 W/ TRIGONOMETRY MIDTERM REVIEW

Math 226A Homework 4 Due Monday, December 11th

Splines. Parameterization of a Curve. Curve Representations. Roller coaster. What Do We Need From Curves in Computer Graphics? Modeling Complex Shapes

CS1114 Assignment 5 Part 1

Natural Quartic Spline

Grade 5 Geometry. Answer t he quest ions. Choose correct answer(s) f rom given choice. For more such worksheets visit

Exploration Assignment #1. (Linear Systems)

Lecture 9: Introduction to Spline Curves

Piecewise Polynomial Interpolation, cont d

Honors Algebra 2 Function Transformations Discovery

A Practical Review of Uniform B-Splines

In this course we will need a set of techniques to represent curves and surfaces in 2-d and 3-d. Some reasons for this include

Georeferencing & Spatial Adjustment

Sketching graphs of polynomials

A Cumulative Averaging Method for Piecewise Polynomial Approximation to Discrete Data

Amplifying an Instructional Task Algebra II Example

Engineering Analysis ENG 3420 Fall Dan C. Marinescu Office: HEC 439 B Office hours: Tu-Th 11:00-12:00

D-Optimal Designs. Chapter 888. Introduction. D-Optimal Design Overview

Finite Element Analysis Prof. Dr. B. N. Rao Department of Civil Engineering Indian Institute of Technology, Madras. Lecture - 24

Fall CSCI 420: Computer Graphics. 4.2 Splines. Hao Li.

TO DUY ANH SHIP CALCULATION

Remark. Jacobs University Visualization and Computer Graphics Lab : ESM4A - Numerical Methods 331

Quadratic Functions. *These are all examples of polynomial functions.

Georeferencing & Spatial Adjustment 2/13/2018

5.2 Properties of Rational functions

QUESTIONS 1 10 MAY BE DONE WITH A CALCULATOR QUESTIONS ARE TO BE DONE WITHOUT A CALCULATOR. Name

Unit: Quadratic Functions

The Problem. Georeferencing & Spatial Adjustment. Nature Of The Problem: For Example: Georeferencing & Spatial Adjustment 9/20/2016

Connected Minimal Acceleration Trigonometric Curves

Unit 2: Functions and Graphs

The Problem. Georeferencing & Spatial Adjustment. Nature of the problem: For Example: Georeferencing & Spatial Adjustment 2/4/2014

Parameterization of triangular meshes

In some applications it may be important that the extrema of the interpolating function are within the extrema of the given data.

Derivative. Bernstein polynomials: Jacobs University Visualization and Computer Graphics Lab : ESM4A - Numerical Methods 313

UNIT 5 QUADRATIC FUNCTIONS Lesson 1: Interpreting Structure in Expressions Instruction

Yimin Math Centre. Year 10 Term 2 Homework. 3.1 Graphs in the number plane The minimum and maximum value of a quadratic function...

CPSC 695. Methods for interpolation and analysis of continuing surfaces in GIS Dr. M. Gavrilova

Splines. Connecting the Dots

MAPI Computer Vision. Multiple View Geometry

Solving Simple Quadratics 1.0 Topic: Solving Quadratics

Moving Beyond Linearity

Quadratic (and higher order) regression on your calculator (TI-82, 83, or 84) NAME:

Section 2.2: Introducing Permutations and Factorial Notation

Lecture IV Bézier Curves

Warm-Up Exercises. Find the x-intercept and y-intercept 1. 3x 5y = 15 ANSWER 5; y = 2x + 7 ANSWER ; 7

An introduction to interpolation and splines

x y

Important Properties of B-spline Basis Functions

Cubic Splines By Dave Slomer

Advanced Graphics. Beziers, B-splines, and NURBS. Alex Benton, University of Cambridge Supported in part by Google UK, Ltd

Transcription:

Multiple-Choice Test Spline Method Interpolation COMPLETE SOLUTION SET 1. The ollowing n data points, ( x ), ( x ),.. ( x, ) 1, y 1, y n y n quadratic spline interpolation the x-data needs to be (A) equally spaced (B) placed in ascending or descending order o x -values (C) integers (D) positive The correct answer is (B). The ollowing n data points, ( x, y 1 1 ), ( x, y ),.. ( ) x n, y n, are given. For conducting, are given. For conducting quadratic spline interpolation the x-data needs to be arranged in ascending or descending order.

. In cubic spline interpolation, (A) the irst derivatives o the splines are continuous at the interior data points (B) the second derivatives o the splines are continuous at the interior data points (C) the irst and the second derivatives o the splines are continuous at the interior data points (D) the third derivatives o the splines are continuous at the interior data points In cubic spline interpolation, the irst and the second derivatives o the splines are continuous at the interior data points. In quadratic spline interpolation, only the irst derivatives o the splines are continuous at the interior data points.

3. The ollowing incomplete y vs. x data is given. x 1 7 y 5 11???????? 3 The data is it by quadratic spline interpolants given by x ax, 1 x ( ) 1 ( x) x + 1x 9, x ( x) bx + cx + d, x ( x) 5x 303x + 98, x 7 where a, b, c, and d are constants. The value o c is most nearly (A) 303. 00 (B) 1. 50 (C) 0.0000 (D) 1.000 Method 1: Since the irst derivatives o two quadratic splines are continuous at the interior points, at x d d ( bx + cx d ) ( x + 1x 9) bx c x + 1 + x () b + c () + 1 8b + c (1) and at x d d bx + cx d bx c 50x 303 ( ) ( 5x 303x + 98) + x () b + c 50() 303 1b + c 3 () Equations (1) and () in matrix orm 8 1 b 1 1 c 3 Solving these equations gives b 0.5 c 0

Method : The third spline bx + cx + d goes through x. However, so does the second spline. We can use this latter knowledge to ind the value o y at x. ( x) x + 1x 9, x () () + 1() 9 15 The third spline bx + cx + d goes through x. Hence b () + c() + d 15 1 b + c + d 15 (1) The third spline bx + cx + d goes through x. However, so does the ourth spline. We can use this latter knowledge to ind the value o y at x. ( x) 5x 303x + 98, x 7 () 5() 303() + 98 10 The third spline bx + cx + d goes through x. Hence b () + c() + d 10 3 b + c + d 10 () Since the irst derivatives o second and third quadratic splines are continuous at the interior points, at x d d ( bx + cx d ) ( x + 1x 9) bx c x + 1 + x () b + c () + 1 8b + c (3) Equations (1), () and (3) are then 1 b + c + d 15 3 b + c + d 10 8b + c + 0d Putting these equations in matrix orm gives 1 1 3 1 b 15 c 10 8 1 0 d Solving the above equations gives b 0.5 c 0 d 19

. The ollowing incomplete y vs. x data is given. where x 1 7 y 5 11???????? 3 The data is it by quadratic spline interpolants given by x ax 1, 1 x, ( ) ( x) x + 1x 9, x ( x) bx + cx + d, x ( x) ex + x + g, x 7 d a, b, c, d, e,, and g are constants. The value o (A) 1. 50 (B). 0000 (C) 3.000 (D) 1.00 Since the spline ( x) x + 1x 9 is valid in the interval x, the derivative at x. is d ( x) x + 1 d (.). + 1 10. + 1 3.000 at x. most nearly is

5. The ollowing incomplete y vs. x data is given. Where x 1 7 y 5 11???????? 3 The data is it by quadratic spline interpolants given by x ax 1, 1 x, ( ) ( x) x + 1x 9, x ( x) bx + cx + d, x ( x) 5x 303x + 98, x 7 a, b, c, and d are constants. What is the value o ( x)? (A) 00 (B) 5.7 (C) 5.750 (D) 8.000 To ind ( x) we must take ( ax ) + ( x + 1x 9) value o the constant a. Since at x, y 11 a 1 11 11+ 1 a Thus, ( x) ( x 1) + ( x + 1x 9) x [( 3 ) ( 3 ) ] 1 but irst we have to ind the [( 1 ) (.75 ) ] + [( 8.583+ 85.75 3) ( 5.3333+ 8 18) ] [.75] + [ 1] 5.75 3 1 x + x + x 9x 3 + 3 3 + 7 9 3 3 + 7 9

. A robot needs to ollow a path that passes consecutively through six points as shown in the igure. To ind the shortest path that is also smooth you would recommend which o the ollowing? (A) Pass a ith order polynomial through the data (B) Pass linear splines through the data (C) Pass quadratic splines through the data (D) Regress the data to a second order polynomial Path o a Robot y 8 7 5 3 1 0 0 5 10 15 x Using linear splines (Choice B) would create a straight-line path between consecutive points. Although this will be the shortest path it will not be smooth. Regressing the data to a second order polynomial (Choice D) will result in a smooth path but it will not pass through all the points. As demonstrated in the ollowing igure, using polynomial interpolation such as choice (A) is a bad idea and will result in a long path. By using quadratic spline interpolation (choice C), the path will be short as well as smooth.

10 8 y 0 0 8 10 1 x Cubic Spline Fith Order Polynomial