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

Size: px
Start display at page:

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

Transcription

1 Shape-preserving piecewise poly. interpolation In some applications it may be important that the extrema of the interpolating function are within the extrema of the given data. For example: If you the data represents a concentration then you may want an interpolant that can only take values between and. Also, one may one to preserve the shape of the data, which usually translates into meaning that the interpolating function should not introduce any local maxima or minima. Piecewise linear interpolation satisfies the above criteria but it does not result in a smooth interpolating function. So, we instead look for a piecewise cubic interpolating function. The resulting method is called PCHIP, which stands for piecewise cubic Hermite interpolating polynomial. This is not a great name.

2 For each interval [x k,x k+ ], k =,...,n, fit a cubic Hermite polynomial to the data H k (x) =b k (x x k ) 3 + c k (x x k ) 2 + d k (x x k )+e k = x k+ k = f k+ x k f k c k = 3 k 2d k d k+ b k = d k 2 k + d k+ h 2 k e k = f k d k = f k

3 For each interval [x k,x k+ ], k =,...,n, fit a cubic Hermite polynomial to the data = x k+ k = f k+ x k f k H k (x) =b k (x x k ) 3 + c k (x x k ) 2 + d k (x x k )+e k c k = 3 k 2d k d k+ b k = d k 2 k + d k+ h 2 k e k = f k d k = f k But, we are not given the derivatives

4 Idea: Start with the piecewise linear interpolant and approximate the derivative at each data point by averaging the slopes of piecewise linear interpolant from the left and right of the point. <latexit sha_base64="br3zudncye6vbywyrksehioaj7s=">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</latexit> <latexit sha_base64="br3zudncye6vbywyrksehioaj7s=">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</latexit> <latexit sha_base64="br3zudncye6vbywyrksehioaj7s=">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</latexit> <latexit sha_base64="br3zudncye6vbywyrksehioaj7s=">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</latexit> How do we average the slopes?

5 Two ideas: Weighted arithmetic averaging: d k = w k k + w k k w k + w k Weighted harmonic averaging: d k = w k w k k + w k + w k k w k =2 + and w k = +2

6 Two ideas: Weighted arithmetic averaging: d k = w k k + w k k w k + w k Gives a shape preserving interpolant Weighted harmonic averaging: d k = w k w k k + w k + w k k w k =2 + and w k = +2

7 <latexit sha_base64="55neak4vo4+xwmpswxfo9aw3f7e=">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</latexit> <latexit sha_base64="55neak4vo4+xwmpswxfo9aw3f7e=">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</latexit> <latexit sha_base64="55neak4vo4+xwmpswxfo9aw3f7e=">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</latexit> <latexit sha_base64="55neak4vo4+xwmpswxfo9aw3f7e=">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</latexit> How do we make maximum/minimum preserving? If the sign of the slopes from the left and right are different then set the derivative to zero: If k k < then set d k =

Interpolation - 2D mapping Tutorial 1: triangulation

Interpolation - 2D mapping Tutorial 1: triangulation Tutorial 1: triangulation Measurements (Zk) at irregular points (xk, yk) Ex: CTD stations, mooring, etc... The known Data How to compute some values on the regular spaced grid points (+)? The unknown data

More information

Reflector profile optimisation using Radiance

Reflector profile optimisation using Radiance Reflector profile optimisation using Radiance 1,4 1,2 1, 8 6 4 2 3. 2.5 2. 1.5 1..5 I csf(1) csf(2). 1 2 3 4 5 6 Giulio ANTONUTTO Krzysztof WANDACHOWICZ page 1 The idea Krzysztof WANDACHOWICZ Giulio ANTONUTTO

More information

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

Derivative. Bernstein polynomials: Jacobs University Visualization and Computer Graphics Lab : ESM4A - Numerical Methods 313 Derivative Bernstein polynomials: 120202: ESM4A - Numerical Methods 313 Derivative Bézier curve (over [0,1]): with differences. being the first forward 120202: ESM4A - Numerical Methods 314 Derivative

More information

Use Derivatives to Sketch the Graph of a Polynomial Function.

Use Derivatives to Sketch the Graph of a Polynomial Function. Applications of Derivatives Curve Sketching (using derivatives): A) Polynomial Functions B) Rational Functions Lesson 5.2 Use Derivatives to Sketch the Graph of a Polynomial Function. Idea: 1) Identify

More information

Positivity Preserving Interpolation of Positive Data by Rational Quadratic Trigonometric Spline

Positivity Preserving Interpolation of Positive Data by Rational Quadratic Trigonometric Spline IOSR Journal of Mathematics (IOSR-JM) e-issn: 2278-5728, p-issn:2319-765x. Volume 10, Issue 2 Ver. IV (Mar-Apr. 2014), PP 42-47 Positivity Preserving Interpolation of Positive Data by Rational Quadratic

More information

Mar. 20 Math 2335 sec 001 Spring 2014

Mar. 20 Math 2335 sec 001 Spring 2014 Mar. 20 Math 2335 sec 001 Spring 2014 Chebyshev Polynomials Definition: For an integer n 0 define the function ( ) T n (x) = cos n cos 1 (x), 1 x 1. It can be shown that T n is a polynomial of degree n.

More information

Increasing and Decreasing Functions. MATH 1003 Calculus and Linear Algebra (Lecture 20) Increasing and Decreasing Functions

Increasing and Decreasing Functions. MATH 1003 Calculus and Linear Algebra (Lecture 20) Increasing and Decreasing Functions Increasing and Decreasing Functions MATH 1003 Calculus and Linear Algebra (Lecture 20) Maosheng Xiong Department of Mathematics, HKUST Suppose y = f (x). 1. f (x) is increasing on an interval a < x < b,

More information

Evaluating the polynomial at a point

Evaluating the polynomial at a point Evaluating the polynomial at a point Recall that we have a data structure for each piecewise polynomial (linear, quadratic, cubic and cubic Hermite). We have a routine that sets evenly spaced interpolation

More information

Curve Representation ME761A Instructor in Charge Prof. J. Ramkumar Department of Mechanical Engineering, IIT Kanpur

Curve Representation ME761A Instructor in Charge Prof. J. Ramkumar Department of Mechanical Engineering, IIT Kanpur Curve Representation ME761A Instructor in Charge Prof. J. Ramkumar Department of Mechanical Engineering, IIT Kanpur Email: jrkumar@iitk.ac.in Curve representation 1. Wireframe models There are three types

More information

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

Remark. Jacobs University Visualization and Computer Graphics Lab : ESM4A - Numerical Methods 331 Remark Reconsidering the motivating example, we observe that the derivatives are typically not given by the problem specification. However, they can be estimated in a pre-processing step. A good estimate

More information

a) y = x 3 + 3x 2 2 b) = UNIT 4 CURVE SKETCHING 4.1 INCREASING AND DECREASING FUNCTIONS

a) y = x 3 + 3x 2 2 b) = UNIT 4 CURVE SKETCHING 4.1 INCREASING AND DECREASING FUNCTIONS UNIT 4 CURVE SKETCHING 4.1 INCREASING AND DECREASING FUNCTIONS We read graphs as we read sentences: left to right. Plainly speaking, as we scan the function from left to right, the function is said to

More information

The following information is for reviewing the material since Exam 3:

The following information is for reviewing the material since Exam 3: Outcomes List for Math 121 Calculus I Fall 2010-2011 General Information: The purpose of this Outcomes List is to give you a concrete summary of the material you should know, and the skills you should

More information

P.5-P.6 Functions & Analyzing Graphs of Functions p.58-84

P.5-P.6 Functions & Analyzing Graphs of Functions p.58-84 P.5-P.6 Functions & Analyzing Graphs of Functions p.58-84 Objectives: Determine whether relations between two variables are functions. Use function notation and evaluate functions. Find the domains of

More information

Section 2.4 Library of Functions; Piecewise-Defined Functions

Section 2.4 Library of Functions; Piecewise-Defined Functions Section. Library of Functions; Piecewise-Defined Functions Objective #: Building the Library of Basic Functions. Graph the following: Ex. f(x) = b; constant function Since there is no variable x in the

More information

2.) What does this graph represent?

2.) What does this graph represent? Standard: A-CED.2 Create equations in two or more variables to represent relationships between quantities; graph equations on coordinate axes with labels and scales. 1.) Write an equation for the graph

More information

COMPUTER AIDED ENGINEERING DESIGN (BFF2612)

COMPUTER AIDED ENGINEERING DESIGN (BFF2612) COMPUTER AIDED ENGINEERING DESIGN (BFF2612) BASIC MATHEMATICAL CONCEPTS IN CAED by Dr. Mohd Nizar Mhd Razali Faculty of Manufacturing Engineering mnizar@ump.edu.my COORDINATE SYSTEM y+ y+ z+ z+ x+ RIGHT

More information

CS 450 Numerical Analysis. Chapter 7: Interpolation

CS 450 Numerical Analysis. Chapter 7: Interpolation Lecture slides based on the textbook Scientific Computing: An Introductory Survey by Michael T. Heath, copyright c 2018 by the Society for Industrial and Applied Mathematics. http://www.siam.org/books/cl80

More information

8 Piecewise Polynomial Interpolation

8 Piecewise Polynomial Interpolation Applied Math Notes by R. J. LeVeque 8 Piecewise Polynomial Interpolation 8. Pitfalls of high order interpolation Suppose we know the value of a function at several points on an interval and we wish to

More information

Four equations are necessary to evaluate these coefficients. Eqn

Four equations are necessary to evaluate these coefficients. Eqn 1.2 Splines 11 A spline function is a piecewise defined function with certain smoothness conditions [Cheney]. A wide variety of functions is potentially possible; polynomial functions are almost exclusively

More information

UNIT 8 STUDY SHEET POLYNOMIAL FUNCTIONS

UNIT 8 STUDY SHEET POLYNOMIAL FUNCTIONS UNIT 8 STUDY SHEET POLYNOMIAL FUNCTIONS KEY FEATURES OF POLYNOMIALS Intercepts of a function o x-intercepts - a point on the graph where y is zero {Also called the zeros of the function.} o y-intercepts

More information

5.1 Introduction to the Graphs of Polynomials

5.1 Introduction to the Graphs of Polynomials Math 3201 5.1 Introduction to the Graphs of Polynomials In Math 1201/2201, we examined three types of polynomial functions: Constant Function - horizontal line such as y = 2 Linear Function - sloped line,

More information

Chapter 4.1 & 4.2 (Part 1) Practice Problems

Chapter 4.1 & 4.2 (Part 1) Practice Problems Chapter 4. & 4. Part Practice Problems EXPECTED SKILLS: Understand how the signs of the first and second derivatives of a function are related to the behavior of the function. Know how to use the first

More information

ALGEBRA II A CURRICULUM OUTLINE

ALGEBRA II A CURRICULUM OUTLINE ALGEBRA II A CURRICULUM OUTLINE 2013-2014 OVERVIEW: 1. Linear Equations and Inequalities 2. Polynomial Expressions and Equations 3. Rational Expressions and Equations 4. Radical Expressions and Equations

More information

Section 4.3: How Derivatives Affect the Shape of the Graph

Section 4.3: How Derivatives Affect the Shape of the Graph Section 4.3: How Derivatives Affect the Shape of the Graph What does the first derivative of a function tell you about the function? Where on the graph below is f x > 0? Where on the graph below is f x

More information

A Modified Spline Interpolation Method for Function Reconstruction from Its Zero-Crossings

A Modified Spline Interpolation Method for Function Reconstruction from Its Zero-Crossings Scientific Papers, University of Latvia, 2010. Vol. 756 Computer Science and Information Technologies 207 220 P. A Modified Spline Interpolation Method for Function Reconstruction from Its Zero-Crossings

More information

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

Engineering Analysis ENG 3420 Fall Dan C. Marinescu Office: HEC 439 B Office hours: Tu-Th 11:00-12:00 Engineering Analysis ENG 3420 Fall 2009 Dan C. Marinescu Office: HEC 439 B Office hours: Tu-Th 11:00-12:00 1 Lecture 24 Attention: The last homework HW5 and the last project are due on Tuesday November

More information

Curves and Surface I. Angel Ch.10

Curves and Surface I. Angel Ch.10 Curves and Surface I Angel Ch.10 Representation of Curves and Surfaces Piece-wise linear representation is inefficient - line segments to approximate curve - polygon mesh to approximate surfaces - can

More information

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

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 Parametric Curves and Surfaces 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 Describing curves in space that objects move

More information

Curves and Surfaces. CS475 / 675, Fall Siddhartha Chaudhuri

Curves and Surfaces. CS475 / 675, Fall Siddhartha Chaudhuri Curves and Surfaces CS475 / 675, Fall 26 Siddhartha Chaudhuri Klein bottle: surface, no edges (Möbius strip: Inductiveload@Wikipedia) Möbius strip: surface, edge Curves and Surfaces Curve: D set Surface:

More information

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

ES 240: Scientific and Engineering Computation. a function f(x) that can be written as a finite series of power functions like Polynomial Deinition a unction () that can be written as a inite series o power unctions like n is a polynomial o order n n ( ) = A polynomial is represented by coeicient vector rom highest power. p=[3-5

More information

Empirical Mode Decomposition Analysis using Rational Splines

Empirical Mode Decomposition Analysis using Rational Splines Empirical Mode Decomposition Analysis using Rational Splines Geoff Pegram Pegram, GGS, MC Peel & TA McMahon, (28). Empirical Mode Decomposition using rational splines: an application to rainfall time series.

More information

Design considerations

Design considerations Curves Design considerations local control of shape design each segment independently smoothness and continuity ability to evaluate derivatives stability small change in input leads to small change in

More information

2.4. A LIBRARY OF PARENT FUNCTIONS

2.4. A LIBRARY OF PARENT FUNCTIONS 2.4. A LIBRARY OF PARENT FUNCTIONS 1 What You Should Learn Identify and graph linear and squaring functions. Identify and graph cubic, square root, and reciprocal function. Identify and graph step and

More information

Second Triangular Hermite Spline Curves and Its Application

Second Triangular Hermite Spline Curves and Its Application Progress in Applied Mathematics Vol. 4, No. 1, 1, pp. [3 36] DOI: 1.3968/j.pam.19558141.1533 ISSN 195-51X [Print] ISSN 195-58 [Online] www.cscanada.net www.cscanada.org Second Triangular Hermite Spline

More information

CS130 : Computer Graphics Curves (cont.) Tamar Shinar Computer Science & Engineering UC Riverside

CS130 : Computer Graphics Curves (cont.) Tamar Shinar Computer Science & Engineering UC Riverside CS130 : Computer Graphics Curves (cont.) Tamar Shinar Computer Science & Engineering UC Riverside Blending Functions Blending functions are more convenient basis than monomial basis canonical form (monomial

More information

Geometric Modeling of Curves

Geometric Modeling of Curves Curves Locus of a point moving with one degree of freedom Locus of a one-dimensional parameter family of point Mathematically defined using: Explicit equations Implicit equations Parametric equations (Hermite,

More information

08 - Designing Approximating Curves

08 - Designing Approximating Curves 08 - Designing Approximating Curves Acknowledgement: Olga Sorkine-Hornung, Alexander Sorkine-Hornung, Ilya Baran Last time Interpolating curves Monomials Lagrange Hermite Different control types Polynomials

More information

Spline Notes. Marc Olano University of Maryland, Baltimore County. February 20, 2004

Spline Notes. Marc Olano University of Maryland, Baltimore County. February 20, 2004 Spline Notes Marc Olano University of Maryland, Baltimore County February, 4 Introduction I. Modeled after drafting tool A. Thin strip of wood or metal B. Control smooth curved path by running between

More information

Objects 2: Curves & Splines Christian Miller CS Fall 2011

Objects 2: Curves & Splines Christian Miller CS Fall 2011 Objects 2: Curves & Splines Christian Miller CS 354 - Fall 2011 Parametric curves Curves that are defined by an equation and a parameter t Usually t [0, 1], and curve is finite Can be discretized at arbitrary

More information

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

Splines. Parameterization of a Curve. Curve Representations. Roller coaster. What Do We Need From Curves in Computer Graphics? Modeling Complex Shapes CSCI 420 Computer Graphics Lecture 8 Splines Jernej Barbic University of Southern California Hermite Splines Bezier Splines Catmull-Rom Splines Other Cubic Splines [Angel Ch 12.4-12.12] Roller coaster

More information

Numerical Methods in Physics Lecture 2 Interpolation

Numerical Methods in Physics Lecture 2 Interpolation Numerical Methods in Physics Pat Scott Department of Physics, Imperial College November 8, 2016 Slides available from http://astro.ic.ac.uk/pscott/ course-webpage-numerical-methods-201617 Outline The problem

More information

Derivation of a polynomial equation for the Natural Earth projection

Derivation of a polynomial equation for the Natural Earth projection Derivation of a polynomial equation for the Natural Earth projection Graduation Thesis Author: Bojan Šavrič Supervisors: Assist. Prof. Dr. Dušan Petrovič, UL FGG Dr. Bernhard Jenny, IKG ETH Zürich Prof.

More information

Introduction to Computer Graphics

Introduction to Computer Graphics Introduction to Computer Graphics 2016 Spring National Cheng Kung University Instructors: Min-Chun Hu 胡敏君 Shih-Chin Weng 翁士欽 ( 西基電腦動畫 ) Data Representation Curves and Surfaces Limitations of Polygons Inherently

More information

Piecewise polynomial interpolation

Piecewise polynomial interpolation Chapter 2 Piecewise polynomial interpolation In ection.6., and in Lab, we learned that it is not a good idea to interpolate unctions by a highorder polynomials at equally spaced points. However, it transpires

More information

Lecture IV Bézier Curves

Lecture IV Bézier Curves Lecture IV Bézier Curves Why Curves? Why Curves? Why Curves? Why Curves? Why Curves? Linear (flat) Curved Easier More pieces Looks ugly Complicated Fewer pieces Looks smooth What is a curve? Intuitively:

More information

Computer Graphics Curves and Surfaces. Matthias Teschner

Computer Graphics Curves and Surfaces. Matthias Teschner Computer Graphics Curves and Surfaces Matthias Teschner Outline Introduction Polynomial curves Bézier curves Matrix notation Curve subdivision Differential curve properties Piecewise polynomial curves

More information

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

Fall CSCI 420: Computer Graphics. 4.2 Splines. Hao Li. Fall 2014 CSCI 420: Computer Graphics 4.2 Splines Hao Li http://cs420.hao-li.com 1 Roller coaster Next programming assignment involves creating a 3D roller coaster animation We must model the 3D curve

More information

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

Interactive Graphics. Lecture 9: Introduction to Spline Curves. Interactive Graphics Lecture 9: Slide 1 Interactive Graphics Lecture 9: Introduction to Spline Curves Interactive Graphics Lecture 9: Slide 1 Interactive Graphics Lecture 13: Slide 2 Splines The word spline comes from the ship building trade

More information

Algebra 4-5 Study Guide: Direct Variation (pp ) Page! 1 of! 9

Algebra 4-5 Study Guide: Direct Variation (pp ) Page! 1 of! 9 Page! 1 of! 9 Attendance Problems. Solve for y. 1. 3 + y = 2x 2. 6x = 3y 3. Write an equation that describes the relationship. Solve for x. 3 4.! 5.! 5 = x 6 15 2 = 1.5 x I can identify, write, and graph

More information

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

February 2017 (1/20) 2 Piecewise Polynomial Interpolation 2.2 (Natural) Cubic Splines. MA378/531 Numerical Analysis II ( NA2 ) f f f f f (/2).9.8.7.6.5.4.3.2. S Knots.7.6.5.4.3.2. 5 5.2.8.6.4.2 S Knots.2 5 5.9.8.7.6.5.4.3.2..9.8.7.6.5.4.3.2. S Knots 5 5 S Knots 5 5 5 5.35.3.25.2.5..5 5 5.6.5.4.3.2. 5 5 4 x 3 3.5 3 2.5 2.5.5 5

More information

Multiple-Choice Test Spline Method Interpolation COMPLETE SOLUTION SET

Multiple-Choice Test Spline Method Interpolation COMPLETE SOLUTION SET 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

More information

APPM/MATH Problem Set 4 Solutions

APPM/MATH Problem Set 4 Solutions APPM/MATH 465 Problem Set 4 Solutions This assignment is due by 4pm on Wednesday, October 16th. You may either turn it in to me in class on Monday or in the box outside my office door (ECOT 35). Minimal

More information

Splines and Piecewise Interpolation. Hsiao-Lung Chan Dept Electrical Engineering Chang Gung University, Taiwan

Splines and Piecewise Interpolation. Hsiao-Lung Chan Dept Electrical Engineering Chang Gung University, Taiwan Splines and Piecewise Interpolation Hsiao-Lung Chan Dept Electrical Engineering Chang Gung University, Taiwan chanhl@mail.cgu.edu.tw Splines n 1 intervals and n data points 2 Splines (cont.) Go through

More information

Module: 2 Finite Element Formulation Techniques Lecture 3: Finite Element Method: Displacement Approach

Module: 2 Finite Element Formulation Techniques Lecture 3: Finite Element Method: Displacement Approach 11 Module: 2 Finite Element Formulation Techniques Lecture 3: Finite Element Method: Displacement Approach 2.3.1 Choice of Displacement Function Displacement function is the beginning point for the structural

More information

Bézier Splines. B-Splines. B-Splines. CS 475 / CS 675 Computer Graphics. Lecture 14 : Modelling Curves 3 B-Splines. n i t i 1 t n i. J n,i.

Bézier Splines. B-Splines. B-Splines. CS 475 / CS 675 Computer Graphics. Lecture 14 : Modelling Curves 3 B-Splines. n i t i 1 t n i. J n,i. Bézier Splines CS 475 / CS 675 Computer Graphics Lecture 14 : Modelling Curves 3 n P t = B i J n,i t with 0 t 1 J n, i t = i=0 n i t i 1 t n i No local control. Degree restricted by the control polygon.

More information

Algebra II Quadratic Functions and Equations - Extrema Unit 05b

Algebra II Quadratic Functions and Equations - Extrema Unit 05b Big Idea: Quadratic Functions can be used to find the maximum or minimum that relates to real world application such as determining the maximum height of a ball thrown into the air or solving problems

More information

Blacksburg, VA July 24 th 30 th, 2010 Georeferencing images and scanned maps Page 1. Georeference

Blacksburg, VA July 24 th 30 th, 2010 Georeferencing images and scanned maps Page 1. Georeference George McLeod Prepared by: With support from: NSF DUE-0903270 in partnership with: Geospatial Technician Education Through Virginia s Community Colleges (GTEVCC) Georeference The process of defining how

More information

FUNCTIONS, ALGEBRA, & DATA ANALYSIS CURRICULUM GUIDE Overview and Scope & Sequence

FUNCTIONS, ALGEBRA, & DATA ANALYSIS CURRICULUM GUIDE Overview and Scope & Sequence FUNCTIONS, ALGEBRA, & DATA ANALYSIS CURRICULUM GUIDE Overview and Scope & Sequence Loudoun County Public Schools 2017-2018 (Additional curriculum information and resources for teachers can be accessed

More information

Dyadic Interpolation Schemes

Dyadic Interpolation Schemes Dyadic Interpolation Schemes Mie Day, January 8 Given a set of equally-spaced samples of some function, we d lie to be able to mae educated guesses for the values which the function would tae on at points

More information

Lecture VIII. Global Approximation Methods: I

Lecture VIII. Global Approximation Methods: I Lecture VIII Global Approximation Methods: I Gianluca Violante New York University Quantitative Macroeconomics G. Violante, Global Methods p. 1 /29 Global function approximation Global methods: function

More information

UNIT 1: NUMBER LINES, INTERVALS, AND SETS

UNIT 1: NUMBER LINES, INTERVALS, AND SETS ALGEBRA II CURRICULUM OUTLINE 2011-2012 OVERVIEW: 1. Numbers, Lines, Intervals and Sets 2. Algebraic Manipulation: Rational Expressions and Exponents 3. Radicals and Radical Equations 4. Function Basics

More information

Sung-Eui Yoon ( 윤성의 )

Sung-Eui Yoon ( 윤성의 ) CS480: Computer Graphics Curves and Surfaces Sung-Eui Yoon ( 윤성의 ) Course URL: http://jupiter.kaist.ac.kr/~sungeui/cg Today s Topics Surface representations Smooth curves Subdivision 2 Smooth Curves and

More information

2D Spline Curves. CS 4620 Lecture 18

2D Spline Curves. CS 4620 Lecture 18 2D Spline Curves CS 4620 Lecture 18 2014 Steve Marschner 1 Motivation: smoothness In many applications we need smooth shapes that is, without discontinuities So far we can make things with corners (lines,

More information

Kevin James. MTHSC 102 Section 4.4 Inflection Points and Second Deriva

Kevin James. MTHSC 102 Section 4.4 Inflection Points and Second Deriva MTHSC 102 Section 4.4 Inflection Points and Second Derivatives Example A model for the population of KY from 1980-1993 is p(x) = 0.395x 3 6.67x 2 +30.3x +3661 thousand people where x is the number of years

More information

CS 475 / CS Computer Graphics. Modelling Curves 3 - B-Splines

CS 475 / CS Computer Graphics. Modelling Curves 3 - B-Splines CS 475 / CS 675 - Computer Graphics Modelling Curves 3 - Bézier Splines n P t = i=0 No local control. B i J n,i t with 0 t 1 J n,i t = n i t i 1 t n i Degree restricted by the control polygon. http://www.cs.mtu.edu/~shene/courses/cs3621/notes/spline/bezier/bezier-move-ct-pt.html

More information

Computer Graphics / Animation

Computer Graphics / Animation Computer Graphics / Animation Artificial object represented by the number of points in space and time (for moving, animated objects). Essential point: How do you interpolate these points in space and time?

More information

LECTURE NOTES - SPLINE INTERPOLATION. 1. Introduction. Problems can arise when a single high-degree polynomial is fit to a large number

LECTURE NOTES - SPLINE INTERPOLATION. 1. Introduction. Problems can arise when a single high-degree polynomial is fit to a large number LECTURE NOTES - SPLINE INTERPOLATION DR MAZHAR IQBAL 1 Introduction Problems can arise when a single high-degree polynomial is fit to a large number of points High-degree polynomials would obviously pass

More information

OUTLINE. Quadratic Bezier Curves Cubic Bezier Curves

OUTLINE. Quadratic Bezier Curves Cubic Bezier Curves BEZIER CURVES 1 OUTLINE Introduce types of curves and surfaces Introduce the types of curves Interpolating Hermite Bezier B-spline Quadratic Bezier Curves Cubic Bezier Curves 2 ESCAPING FLATLAND Until

More information

12 and the critical numbers of f ( )

12 and the critical numbers of f ( ) Math 1314 Lesson 15 Second Derivative Test and Optimization There is a second derivative test to find relative extrema. It is sometimes convenient to use; however, it can be inconclusive. Later in the

More information

Sec.4.1 Increasing and Decreasing Functions

Sec.4.1 Increasing and Decreasing Functions U4L1: Sec.4.1 Increasing and Decreasing Functions A function is increasing on a particular interval if for any, then. Ie: As x increases,. A function is decreasing on a particular interval if for any,

More information

Interpolation and Basis Fns

Interpolation and Basis Fns CS148: Introduction to Computer Graphics and Imaging Interpolation and Basis Fns Topics Today Interpolation Linear and bilinear interpolation Barycentric interpolation Basis functions Square, triangle,,

More information

(f) Find an interval over which f is concave upwards.

(f) Find an interval over which f is concave upwards. April 4, 2005 Name The total number of points available is 157. work. Throughout this test, show your 1. (24 points) Consider the function f(x) = 2x+9. For this function there are two 6x+3 important intervals:

More information

Polynomials tend to oscillate (wiggle) a lot, even when our true function does not.

Polynomials tend to oscillate (wiggle) a lot, even when our true function does not. AMSC/CMSC 460 Computational Methods, Fall 2007 UNIT 2: Spline Approximations Dianne P O Leary c 2001, 2002, 2007 Piecewise polynomial interpolation Piecewise polynomial interpolation Read: Chapter 3 Skip:

More information

1.1 Pearson Modeling and Equation Solving

1.1 Pearson Modeling and Equation Solving Date:. Pearson Modeling and Equation Solving Syllabus Objective:. The student will solve problems using the algebra of functions. Modeling a Function: Numerical (data table) Algebraic (equation) Graphical

More information

THE STUDY OF NEW APPROACHES IN CUBIC SPLINE INTERPOLATION FOR AUTO MOBILE DATA

THE STUDY OF NEW APPROACHES IN CUBIC SPLINE INTERPOLATION FOR AUTO MOBILE DATA Journal of Science and Arts Year 17, No. 3(4), pp. 41-46, 217 ORIGINAL PAPER THE STUDY OF NEW APPROACHES IN CUBIC SPLINE INTERPOLATION FOR AUTO MOBILE DATA NAJMUDDIN AHMAD 1, KHAN FARAH DEEBA 1 Manuscript

More information

Monotonic Cubic Spline Interpolation

Monotonic Cubic Spline Interpolation Monotonic Cubic Spline Interpolation George Wolberg Itzik Alfy Department of Computer Science City College of New York / CUNY New York, NY wolberg@cs-mailengrccnycunyedu Abstract This paper describes the

More information

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

Lecture 8. Divided Differences,Least-Squares Approximations. Ceng375 Numerical Computations at December 9, 2010 Lecture 8, Ceng375 Numerical Computations at December 9, 2010 Computer Engineering Department Çankaya University 8.1 Contents 1 2 3 8.2 : These provide a more efficient way to construct an interpolating

More information

Bezier Curves, B-Splines, NURBS

Bezier Curves, B-Splines, NURBS Bezier Curves, B-Splines, NURBS Example Application: Font Design and Display Curved objects are everywhere There is always need for: mathematical fidelity high precision artistic freedom and flexibility

More information

ME 261: Numerical Analysis Lecture-12: Numerical Interpolation

ME 261: Numerical Analysis Lecture-12: Numerical Interpolation 1 ME 261: Numerical Analysis Lecture-12: Numerical Interpolation Md. Tanver Hossain Department of Mechanical Engineering, BUET http://tantusher.buet.ac.bd 2 Inverse Interpolation Problem : Given a table

More information

lecture 10: B-Splines

lecture 10: B-Splines 9 lecture : -Splines -Splines: a basis for splines Throughout our discussion of standard polynomial interpolation, we viewed P n as a linear space of dimension n +, and then expressed the unique interpolating

More information

Regularity Analysis of Non Uniform Data

Regularity Analysis of Non Uniform Data Regularity Analysis of Non Uniform Data Christine Potier and Christine Vercken Abstract. A particular class of wavelet, derivatives of B-splines, leads to fast and ecient algorithms for contours detection

More information

Chapter 1 Notes, Calculus I with Precalculus 3e Larson/Edwards

Chapter 1 Notes, Calculus I with Precalculus 3e Larson/Edwards Contents 1.1 Functions.............................................. 2 1.2 Analzing Graphs of Functions.................................. 5 1.3 Shifting and Reflecting Graphs..................................

More information

2D Spline Curves. CS 4620 Lecture 13

2D Spline Curves. CS 4620 Lecture 13 2D Spline Curves CS 4620 Lecture 13 2008 Steve Marschner 1 Motivation: smoothness In many applications we need smooth shapes [Boeing] that is, without discontinuities So far we can make things with corners

More information

B-Spline Polynomials. B-Spline Polynomials. Uniform Cubic B-Spline Curves CS 460. Computer Graphics

B-Spline Polynomials. B-Spline Polynomials. Uniform Cubic B-Spline Curves CS 460. Computer Graphics CS 460 B-Spline Polynomials Computer Graphics Professor Richard Eckert March 24, 2004 B-Spline Polynomials Want local control Smoother curves B-spline curves: Segmented approximating curve 4 control points

More information

Math 1314 Lesson 12 Curve Analysis (Polynomials)

Math 1314 Lesson 12 Curve Analysis (Polynomials) Math 1314 Lesson 12 Curve Analysis (Polynomials) This lesson will cover analyzing polynomial functions using GeoGebra. Suppose your company embarked on a new marketing campaign and was able to track sales

More information

Calculators ARE NOT Permitted On This Portion Of The Exam 28 Questions - 55 Minutes

Calculators ARE NOT Permitted On This Portion Of The Exam 28 Questions - 55 Minutes 1 of 11 1) Give f(g(1)), given that Calculators ARE NOT Permitted On This Portion Of The Exam 28 Questions - 55 Minutes 2) Find the slope of the tangent line to the graph of f at x = 4, given that 3) Determine

More information

Math 225 Scientific Computing II Outline of Lectures

Math 225 Scientific Computing II Outline of Lectures Math 225 Scientific Computing II Outline of Lectures Spring Semester 2003 I. Interpolating polynomials Lagrange formulation of interpolating polynomial Uniqueness of interpolating polynomial of degree

More information

GL9: Engineering Communications. GL9: CAD techniques. Curves Surfaces Solids Techniques

GL9: Engineering Communications. GL9: CAD techniques. Curves Surfaces Solids Techniques 436-105 Engineering Communications GL9:1 GL9: CAD techniques Curves Surfaces Solids Techniques Parametric curves GL9:2 x = a 1 + b 1 u + c 1 u 2 + d 1 u 3 + y = a 2 + b 2 u + c 2 u 2 + d 2 u 3 + z = a

More information

Natural Quartic Spline

Natural Quartic Spline Natural Quartic Spline Rafael E Banchs INTRODUCTION This report describes the natural quartic spline algorithm developed for the enhanced solution of the Time Harmonic Field Electric Logging problem As

More information

Friday, 11 January 13. Interpolation

Friday, 11 January 13. Interpolation Interpolation Interpolation Interpolation is not a branch of mathematic but a collection of techniques useful for solving computer graphics problems Basically an interpolant is a way of changing one number

More information

Math 1314 Lesson 12 Curve Analysis (Polynomials)

Math 1314 Lesson 12 Curve Analysis (Polynomials) Math 1314 Lesson 12 Curve Analysis (Polynomials) This lesson will cover analyzing polynomial functions using GeoGebra. Suppose your company embarked on a new marketing campaign and was able to track sales

More information

TASC Test Mathematics

TASC Test Mathematics Tutorial Outline TASC Test Assessing Secondary Completion Tutorials are based on specifications found in TASC Test information for publishers which includes alignment to Common Core State Standards and

More information

3D Modeling Parametric Curves & Surfaces

3D Modeling Parametric Curves & Surfaces 3D Modeling Parametric Curves & Surfaces Shandong University Spring 2012 3D Object Representations Raw data Point cloud Range image Polygon soup Solids Voxels BSP tree CSG Sweep Surfaces Mesh Subdivision

More information

Remember to SHOW ALL STEPS. You must be able to solve analytically. Answers are shown after each problem under A, B, C, or D.

Remember to SHOW ALL STEPS. You must be able to solve analytically. Answers are shown after each problem under A, B, C, or D. Math 165 - Review Chapters 3 and 4 Name Remember to SHOW ALL STEPS. You must be able to solve analytically. Answers are shown after each problem under A, B, C, or D. Find the quadratic function satisfying

More information

Math 1314 Lesson 12 Curve Analysis (Polynomials) This lesson will cover analyzing polynomial functions using GeoGebra.

Math 1314 Lesson 12 Curve Analysis (Polynomials) This lesson will cover analyzing polynomial functions using GeoGebra. Math 1314 Lesson 12 Curve Analysis (Polynomials) This lesson will cover analyzing polynomial functions using GeoGebra. Suppose your company embarked on a new marketing campaign and was able to track sales

More information

MEI Desmos Tasks for AS Pure

MEI Desmos Tasks for AS Pure Task 1: Coordinate Geometry Intersection of a line and a curve 1. Add a quadratic curve, e.g. y = x² 4x + 1 2. Add a line, e.g. y = x 3 3. Select the points of intersection of the line and the curve. What

More information

(1) di=g(ai_,ai), =2,...,n-l, A METHOD FOR CONSTRUCTING LOCAL MONOTONE PIECEWISE CUBIC INTERPOLANTS*

(1) di=g(ai_,ai), =2,...,n-l, A METHOD FOR CONSTRUCTING LOCAL MONOTONE PIECEWISE CUBIC INTERPOLANTS* SIAM J. ScI. STAT. COMPUT. Vol. 5, No. 2, June 1984 (C) 1984 Society for Industrial and Applied Mathematics 0O4 A METHOD FOR CONSTRUCTING LOCAL MONOTONE PIECEWISE CUBIC INTERPOLANTS* F. N. FRITSCH" AND

More information

Central issues in modelling

Central issues in modelling Central issues in modelling Construct families of curves, surfaces and volumes that can represent common objects usefully; are easy to interact with; interaction includes: manual modelling; fitting to

More information

Natural Numbers and Integers. Big Ideas in Numerical Methods. Overflow. Real Numbers 29/07/2011. Taking some ideas from NM course a little further

Natural Numbers and Integers. Big Ideas in Numerical Methods. Overflow. Real Numbers 29/07/2011. Taking some ideas from NM course a little further Natural Numbers and Integers Big Ideas in Numerical Methods MEI Conference 2011 Natural numbers can be in the range [0, 2 32 1]. These are known in computing as unsigned int. Numbers in the range [ (2

More information

Multimodal Elastic Image Matching

Multimodal Elastic Image Matching Research results based on my diploma thesis supervised by Prof. Witsch 2 and in cooperation with Prof. Mai 3. 1 February 22 nd 2011 1 Karlsruhe Institute of Technology (KIT) 2 Applied Mathematics Department,

More information