Cubic Spline Questions
|
|
- Neil Smith
- 6 years ago
- Views:
Transcription
1 Cubic Spline Questions. Find natural cubic splines which interpolate the following dataset of, points:.0,.,.,.0, 7.0,.,.0,0.; estimate the value for. Solution: Step : Use the n- cubic spline equations to find the second derivatives slide 0: : : Natural splines have 0 so the sstem simplifies to: Step : ppl these solutions to obtain the cubic spline equations from formulae for,, C, slides 7 & 77 for the three subintervals i.e., with,,. For :...0 C [ ]. [ ].
2 The spline equation, which applied for the first subinterval.0 < <., is then given b: C [ ].7 S For : C [ ]7.0. [ ]7.0. The spline equation, which applied for the second subinterval. < < 7.0, is then given b:..0. [. [ ] C 0. 7 ] S For : C [ ] [ 7 ].0 7.0
3 The spline equation, which applied for the third subinterval 7.0 < <.0, is then given b: C [ ]. 0 S The three equations S, S and S constitute the natural cubic spline equations for over the interval.0 < < To estimate the value at, use the spline equation for the second sub-interval S:
4 . Find the interpolating cubic splines for the five logarithmic breakpoints,ln,,ln,,ln,,ln, and,ln. Use [i.e. three eercises to do here]: a natural endpoint conditions; b specified endslopes of at and / at ; and c not-a-knot conditions. Compare the graphs corresponding to the three different endpoint conditions. For whichever of these endpoint conditions can be used with the built-in Matlab function, compare our solution to that found with Matlab. Solution: Step : Use the n- cubic spline equations to find the second derivatives. We end up with the following sstem of equations denoted Sstem : ln ln ln ln ln : ln ln ln ln ln : ln ln ln ln ln : Step : Find,, C, slides 7 & 77 for the four subintervals. For : ] [ C ] [
5 For : ] [ C ] [ For : ] [ C ] [ For : ] [ C ] [
6 a Using natural endpoint conditions Natural splines have 0 so Sstem simplifies to: ln ln 0 ln The spline equation, which applied for the first subinterval < <, is then given b: C ln ln 0 [ ] 0. S The spline equation, which applied for the second subinterval < <, is then given b: C ln ln [ ] 0. [ ] 0.00 S The spline equation, which applied for the third subinterval < <, is then given b: C ln ln [ ] 0.00 [ ] S The spline equation, which applied for the fourth subinterval < <, is then given b: C ln ln [ ] S
7 b Using specified endslopes of at and / at NOTE: There was a tpo on the Web, the endslope at is not zero! We need to set the values of & to values calculated from equation [] from slide 7 in the notes so that & have the desired values. For the left endpoint, use. For the right endpoint, use. d d where and d t, : d t, d d : ln ln 0 ln ln ln 0 ln With these conditions, Sstem simplifies to: ln ln ln ln ln The spline equation, which applied for the first subinterval < <, is then given b: C ln ln [ ] 0. [ ] 0.7 S
8 The spline equation, which applied for the second subinterval < <, is then given b: C ln ln [ ] 0.7 [ ] 0. S The spline equation, which applied for the third subinterval < <, is then given b: C ln ln [ ] 0. [ ] S The spline equation, which applied for the fourth subinterval < <, is then given b: ln [ C ln [ ] ] S c Using not-a-knot conditions We wish to enforce the continuit of the third derivative at the first and last internal knots i.e., and. To begin, we take the derivative of the second derivative found on slide 7: d d d d Continuit at these internal knots mean: t : 0 t : 0
9 With these conditions, Sstem simplifies to: 0 ln ln ln The spline equation, which applied for the first subinterval < <, is then given b: C ln ln [ ] 0. [ ] 0.77 S The spline equation, which applied for the second subinterval < <, is then given b: C ln ln [ ] 0.77 [ ] 0.0 S The spline equation, which applied for the third subinterval < <, is then given b: C ln ln [ ] 0.0 [ ] 0.0 S The spline equation, which applied for the fourth subinterval < <, is then given b: ln [ 0.00 C ln [ ] ] S
10 Please note that with this last case, since we are using the not-a-knot conditions, S and S are in fact the same cubic function, as is the case with S and S. Therefore, if ou are confident in our results, ou actuall onl need to find two spline equations for this question when using the not-a-knot conditions! In each case, the four equations S, S, S and S constitute the natural cubic spline equations for over the interval < <. The following are the plots of these splines in Matlab. The built-in spline function in Matlab is capable of finding splines using the fied endslopes condition and the not-aknot condition.. Cublic spline using natural endpoints
11 . Cublic spline using fied endslopes hand dotted Matlab spline function solid Cublic spline using not-a-knot conditions hand dotted Matlab spline function solid
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 informationHandout 4 - Interpolation Examples
Handout 4 - Interpolation Examples Middle East Technical University Example 1: Obtaining the n th Degree Newton s Interpolating Polynomial Passing through (n+1) Data Points Obtain the 4 th degree Newton
More information7. f(x) = 1 2 x f(x) = x f(x) = 4 x at x = 10, 8, 6, 4, 2, 0, 2, and 4.
Section 2.2 The Graph of a Function 109 2.2 Eercises Perform each of the following tasks for the functions defined b the equations in Eercises 1-8. i. Set up a table of points that satisf the given equation.
More informationNatural 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 informationCubic spline interpolation
Cubic spline interpolation In the following, we want to derive the collocation matrix for cubic spline interpolation. Let us assume that we have equidistant knots. To fulfill the Schoenberg-Whitney condition
More informationAPPM/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 informationMath 226A Homework 4 Due Monday, December 11th
Math 226A Homework 4 Due Monday, December 11th 1. (a) Show that the polynomial 2 n (T n+1 (x) T n 1 (x)), is the unique monic polynomial of degree n + 1 with roots at the Chebyshev points x k = cos ( )
More informationRemark. 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 information8 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 information9. f(x) = x f(x) = x g(x) = 2x g(x) = 5 2x. 13. h(x) = 1 3x. 14. h(x) = 2x f(x) = x x. 16.
Section 4.2 Absolute Value 367 4.2 Eercises For each of the functions in Eercises 1-8, as in Eamples 7 and 8 in the narrative, mark the critical value on a number line, then mark the sign of the epression
More information6. f(x) = x f(x) = x f(x) = x f(x) = 3 x. 10. f(x) = x + 3
Section 9.1 The Square Root Function 879 9.1 Eercises In Eercises 1-, complete each of the following tasks. i. Set up a coordinate sstem on a sheet of graph paper. Label and scale each ais. ii. Complete
More informationInterpolation - 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 informationHomework #6 Brief Solutions 2012
Homework #6 Brief Solutions %page 95 problem 4 data=[-,;-,;,;4,] data = - - 4 xk=data(:,);yk=data(:,);s=csfit(xk,yk,-,) %Using the program to find the coefficients S =.456 -.456 -.. -.5.9 -.5484. -.58.87.
More informationFebruary 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 informationInterpolation & Polynomial Approximation. Cubic Spline Interpolation II
Interpolation & Polynomial Approximation Cubic Spline Interpolation II Numerical Analysis (9th Edition) R L Burden & J D Faires Beamer Presentation Slides prepared by John Carroll Dublin City University
More informationIntermediate Algebra. Gregg Waterman Oregon Institute of Technology
Intermediate Algebra Gregg Waterman Oregon Institute of Technolog c 2017 Gregg Waterman This work is licensed under the Creative Commons Attribution 4.0 International license. The essence of the license
More informationMar. 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 informationEngineering 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 informationGraphing Equations. The Rectangular Coordinate System
3.1 Graphing Equations The Rectangular Coordinate Sstem Ordered pair two numbers associated with a point on a graph. The first number gives the horizontal location of the point. The second gives the vertical
More informationImportant Properties of B-spline Basis Functions
Important Properties of B-spline Basis Functions P2.1 N i,p (u) = 0 if u is outside the interval [u i, u i+p+1 ) (local support property). For example, note that N 1,3 is a combination of N 1,0, N 2,0,
More informationLinear Interpolating Splines
Jim Lambers MAT 772 Fall Semester 2010-11 Lecture 17 Notes Tese notes correspond to Sections 112, 11, and 114 in te text Linear Interpolating Splines We ave seen tat ig-degree polynomial interpolation
More informationNumerical 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 informationSection 9.3: Functions and their Graphs
Section 9.: Functions and their Graphs Graphs provide a wa of displaing, interpreting, and analzing data in a visual format. In man problems, we will consider two variables. Therefore, we will need to
More information8.2 Exercises. Section 8.2 Exponential Functions 783
Section 8.2 Eponential Functions 783 8.2 Eercises 1. The current population of Fortuna is 10,000 heart souls. It is known that the population is growing at a rate of 4% per ear. Assuming this rate remains
More informationGraphs, Linear Equations, and Functions
Graphs, Linear Equations, and Functions. The Rectangular R. Coordinate Fractions Sstem bjectives. Interpret a line graph.. Plot ordered pairs.. Find ordered pairs that satisf a given equation. 4. Graph
More informationChapter 3. Interpolation. 3.1 Introduction
Chapter 3 Interpolation 3 Introduction One of the fundamental problems in Numerical Methods is the problem of interpolation, that is given a set of data points ( k, k ) for k =,, n, how do we find a function
More informationChapter 1. Limits and Continuity. 1.1 Limits
Chapter Limits and Continuit. Limits The its is the fundamental notion of calculus. This underling concept is the thread that binds together virtuall all of the calculus ou are about to stud. In this section,
More informationSection 1.4 Limits involving infinity
Section. Limits involving infinit (/3/08) Overview: In later chapters we will need notation and terminolog to describe the behavior of functions in cases where the variable or the value of the function
More informationSet 5, Total points: 100 Issued: week of
Prof. P. Koumoutsakos Prof. Dr. Jens Walther ETH Zentrum, CLT F 1, E 11 CH-809 Zürich Models, Algorithms and Data (MAD): Introduction to Computing Spring semester 018 Set 5, Total points: 100 Issued: week
More informationTransformations of Functions. 1. Shifting, reflecting, and stretching graphs Symmetry of functions and equations
Chapter Transformations of Functions TOPICS.5.. Shifting, reflecting, and stretching graphs Smmetr of functions and equations TOPIC Horizontal Shifting/ Translation Horizontal Shifting/ Translation Shifting,
More informationLESSON 5.3 SYSTEMS OF INEQUALITIES
LESSON 5. SYSTEMS OF INEQUALITIES LESSON 5. SYSTEMS OF INEQUALITIES OVERVIEW Here s what ou ll learn in this lesson: Solving Linear Sstems a. Solving sstems of linear inequalities b graphing As a conscientious
More informationInterpolation by Spline Functions
Interpolation by Spline Functions Com S 477/577 Sep 0 007 High-degree polynomials tend to have large oscillations which are not the characteristics of the original data. To yield smooth interpolating curves
More information1. y = f(x) y = f(x + 3) 3. y = f(x) y = f(x 1) 5. y = 3f(x) 6. y = f(3x) 7. y = f(x) 8. y = f( x) 9. y = f(x 3) + 1
.7 Transformations.7. Eercises To see all of the help resources associated with this section, click OSttS Chapter b. Suppose (, ) is on the graph of = f(). In Eercises - 8, use Theorem.7 to find a point
More informationCS 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 informationME 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 informationlecture 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 informationA SCATTERED DATA INTERPOLANT FOR THE SOLUTION OF THREE-DIMENSIONAL PDES
European Conference on Computational Fluid Dnamics ECCOMAS CFD 26 P. Wesseling, E. Oñate and J. Périau (Eds) c TU Delft, The Netherlands, 26 A SCATTERED DATA INTERPOLANT FOR THE SOLUTION OF THREE-DIMENSIONAL
More informationInterpolation and Splines
Interpolation and Splines Anna Gryboś October 23, 27 1 Problem setting Many of physical phenomenona are described by the functions that we don t know exactly. Often we can calculate or measure the values
More information14.1. It s very difficult to visualize a function f of three variables by its graph, since that
+ +@= + +@=4 SECTION 4. FUNCTIONS OF SEVERAL VARIABLES 86 It s ver difficult to visualie a function f of three variables b its graph, since that would lie in a four-dimensional space. However, we do gain
More informationJustify all your answers and write down all important steps. Unsupported answers will be disregarded.
Numerical Analysis FMN011 2017/05/30 The exam lasts 5 hours and has 15 questions. A minimum of 35 points out of the total 70 are required to get a passing grade. These points will be added to those you
More informationAppendix C: Review of Graphs, Equations, and Inequalities
Appendi C: Review of Graphs, Equations, and Inequalities C. What ou should learn Just as ou can represent real numbers b points on a real number line, ou can represent ordered pairs of real numbers b points
More informationTable for Third-Degree Spline Interpolation Using Equi-Spaced Knots. By W. D. Hoskins
MATHEMATICS OF COMPUTATION, VOLUME 25, NUMBER 116, OCTOBER, 1971 Table for Third-Degree Spline Interpolation Using Equi-Spaced Knots By W. D. Hoskins Abstract. A table is given for the calculation of the
More information(0, 2) y = x 1 2. y = x (2, 2) y = 2x + 2
.5 Equations of Parallel and Perpendicular Lines COMMON CORE Learning Standards HSG-GPE.B.5 HSG-GPE.B. Essential Question How can ou write an equation of a line that is parallel or perpendicular to a given
More informationDerivative. 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 informationThree-Dimensional Object Representations Chapter 8
Three-Dimensional Object Representations Chapter 8 3D Object Representation A surace can be analticall generated using its unction involving the coordinates. An object can be represented in terms o its
More informationSection 5.5 Piecewise Interpolation
Section 5.5 Piecewise Interpolation Key terms Runge phenomena polynomial wiggle problem Piecewise polynomial interpolation We have considered polynomial interpolation to sets of distinct data like {( )
More informationRational Bezier Surface
Rational Bezier Surface The perspective projection of a 4-dimensional polynomial Bezier surface, S w n ( u, v) B i n i 0 m j 0, u ( ) B j m, v ( ) P w ij ME525x NURBS Curve and Surface Modeling Page 97
More informationPolynomials 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 informationLesson 2.1 Exercises, pages 90 96
Lesson.1 Eercises, pages 9 96 A. a) Complete the table of values. 1 1 1 1 1. 1 b) For each function in part a, sketch its graph then state its domain and range. For : the domain is ; and the range is.
More informationInterpolation. TANA09 Lecture 7. Error analysis for linear interpolation. Linear Interpolation. Suppose we have a table x x 1 x 2...
TANA9 Lecture 7 Interpolation Suppose we have a table x x x... x n+ Interpolation Introduction. Polynomials. Error estimates. Runge s phenomena. Application - Equation solving. Spline functions and interpolation.
More information1 Points and Distances
Ale Zorn 1 Points and Distances 1. Draw a number line, and plot and label these numbers: 0, 1, 6, 2 2. Plot the following points: (A) (3,1) (B) (2,5) (C) (-1,1) (D) (2,-4) (E) (-3,-3) (F) (0,4) (G) (-2,0)
More informationLECTURE 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 informationMATH 122 FINAL EXAM WINTER March 15, 2011
MATH 1 FINAL EXAM WINTER 010-011 March 15, 011 NAME: SECTION: ONLY THE CORRECT ANSWER AND ALL WORK USED TO REACH IT WILL EARN FULL CREDIT. Simplify all answers as much as possible unless explicitly stated
More informationPositivity 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 informationES 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 informationx=2 26. y 3x Use calculus to find the area of the triangle with the given vertices. y sin x cos 2x dx 31. y sx 2 x dx
4 CHAPTER 6 APPLICATIONS OF INTEGRATION 6. EXERCISES 4 Find the area of the shaded region.. =5-. (4, 4) =. 4. = - = (_, ) = -4 =œ + = + =.,. sin,. cos, sin,, 4. cos, cos, 5., 6., 7.,, 4, 8., 8, 4 4, =_
More informationInteractive 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 informationLecture 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 informationCubic Splines and Matlab
Cubic Splines and Matlab October 7, 2006 1 Introduction In this section, we introduce the concept of the cubic spline, and how they are implemented in Matlab. Of particular importance are the new Matlab
More informationBayesian Background Estimation
Bayesian Background Estimation mum knot spacing was determined by the width of the signal structure that one wishes to exclude from the background curve. This paper extends the earlier work in two important
More informationf( x ), or a solution to the equation f( x) 0. You are already familiar with ways of solving
The Bisection Method and Newton s Method. If f( x ) a function, then a number r for which f( r) 0 is called a zero or a root of the function f( x ), or a solution to the equation f( x) 0. You are already
More informationMany logarithms may be calculated by converting them to exponential form. Suppose we want to calculate the value of log. log 16?
Question : How do you evaluate a arithm? Many arithms may be calculated by converting them to exponential form. Suppose we want to calculate the value of arithmic form, 16. Start by writing this expression
More informationGraphing Method. Graph of x + y < > y 10. x
Graphing Method Eample: Graph the inequalities on the same plane: + < 6 and 2 - > 4. Before we graph them simultaneousl, let s look at them separatel. 10-10 10 Graph of + < 6. ---> -10 Graphing Method
More informationName Class Date. subtract 3 from each side. w 5z z 5 2 w p - 9 = = 15 + k = 10m. 10. n =
Reteaching Solving Equations To solve an equation that contains a variable, find all of the values of the variable that make the equation true. Use the equalit properties of real numbers and inverse operations
More information20 Calculus and Structures
0 Calculus and Structures CHAPTER FUNCTIONS Calculus and Structures Copright LESSON FUNCTIONS. FUNCTIONS A function f is a relationship between an input and an output and a set of instructions as to how
More informationComputational Physics PHYS 420
Computational Physics PHYS 420 Dr Richard H. Cyburt Assistant Professor of Physics My office: 402c in the Science Building My phone: (304) 384-6006 My email: rcyburt@concord.edu My webpage: www.concord.edu/rcyburt
More informationUnit 1 Day 4 Notes Piecewise Functions
AFM Unit 1 Day 4 Notes Piecewise Functions Name Date We have seen many graphs that are expressed as single equations and are continuous over a domain of the Real numbers. We have also seen the "discrete"
More informationFunctions: The domain and range
Mathematics Learning Centre Functions: The domain and range Jackie Nicholas Jacquie Hargreaves Janet Hunter c 6 Universit of Sdne Mathematics Learning Centre, Universit of Sdne Functions In these notes
More informationAsymptotic Error Analysis
Asymptotic Error Analysis Brian Wetton Mathematics Department, UBC www.math.ubc.ca/ wetton PIMS YRC, June 3, 2014 Outline Overview Some History Romberg Integration Cubic Splines - Periodic Case More History:
More informationA Cumulative Averaging Method for Piecewise Polynomial Approximation to Discrete Data
Applied Mathematical Sciences, Vol. 1, 16, no. 7, 331-343 HIKARI Ltd, www.m-hiari.com http://dx.doi.org/1.1988/ams.16.5177 A Cumulative Averaging Method for Piecewise Polynomial Approximation to Discrete
More informationCITS2401 Computer Analysis & Visualisation
FACULTY OF ENGINEERING, COMPUTING AND MATHEMATICS CITS2401 Computer Analysis & Visualisation SCHOOL OF COMPUTER SCIENCE AND SOFTWARE ENGINEERING Topic 13 Revision Notes CAV review Topics Covered Sample
More informationBézier 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 information1. Solve the following equation, please show your steps for full credit: (3.1)
Ope Steiner Test 1 Practice Test Identif the choice that best completes the statement or answers the question. 1. Solve the following equation, please show our steps for full credit: (3.1) 1 1 (x + 5)
More information8.6 Three-Dimensional Cartesian Coordinate System
SECTION 8.6 Three-Dimensional Cartesian Coordinate Sstem 69 What ou ll learn about Three-Dimensional Cartesian Coordinates Distance and Midpoint Formulas Equation of a Sphere Planes and Other Surfaces
More informationConsider functions such that then satisfies these properties: So is represented by the cubic polynomials on on and on.
1 of 9 3/1/2006 2:28 PM ne previo Next: Trigonometric Interpolation Up: Spline Interpolation Previous: Piecewise Linear Case Cubic Splines A piece-wise technique which is very popular. Recall the philosophy
More informationHomework #6 Brief Solutions 2011
Homework #6 Brief Solutions %page 95 problem 4 data=[-,;-,;,;4,] data = - - 4 xk=data(:,);yk=data(:,);s=csfit(xk,yk,-,) %Using the program to find the coefficients S =.456 -.456 -.. -.5.9 -.5484. -.58.87.
More information4. Two Dimensional Transformations
4. Two Dimensional Transformations CS362 Introduction to Computer Graphics Helena Wong, 2 In man applications, changes in orientations, sizes, and shapes are accomplished with geometric transformations
More informationRational Bezier Curves
Rational Bezier Curves Use of homogeneous coordinates Rational spline curve: define a curve in one higher dimension space, project it down on the homogenizing variable Mathematical formulation: n P(u)
More informationEvaluating 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 informationAssignment 2. with (a) (10 pts) naive Gauss elimination, (b) (10 pts) Gauss with partial pivoting
Assignment (Be sure to observe the rules about handing in homework). Solve: with (a) ( pts) naive Gauss elimination, (b) ( pts) Gauss with partial pivoting *You need to show all of the steps manually.
More information12.4 The Ellipse. Standard Form of an Ellipse Centered at (0, 0) (0, b) (0, -b) center
. The Ellipse The net one of our conic sections we would like to discuss is the ellipse. We will start b looking at the ellipse centered at the origin and then move it awa from the origin. Standard Form
More informationCurves and Surfaces 1
Curves and Surfaces 1 Representation of Curves & Surfaces Polygon Meshes Parametric Cubic Curves Parametric Bi-Cubic Surfaces Quadric Surfaces Specialized Modeling Techniques 2 The Teapot 3 Representing
More informationDoubly Cyclic Smoothing Splines and Analysis of Seasonal Daily Pattern of CO2 Concentration in Antarctica
Boston-Keio Workshop 2016. Doubly Cyclic Smoothing Splines and Analysis of Seasonal Daily Pattern of CO2 Concentration in Antarctica... Mihoko Minami Keio University, Japan August 15, 2016 Joint work with
More informationGeneralised Mean Averaging Interpolation by Discrete Cubic Splines
Publ. RIMS, Kyoto Univ. 30 (1994), 89-95 Generalised Mean Averaging Interpolation by Discrete Cubic Splines By Manjulata SHRIVASTAVA* Abstract The aim of this work is to introduce for a discrete function,
More informationAnalysis Techniques: Flood Analysis Tutorial with Instaneous Peak Flow Data (Log-Pearson Type III Distribution)
Analysis Techniques: Flood Analysis Tutorial with Instaneous Peak Flow Data (Log-Pearson Type III Distribution) Information to get started: The lesson below contains step-by-step instructions and "snapshots"
More informationCS 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 informationSection 4.2 Graphing Lines
Section. Graphing Lines Objectives In this section, ou will learn to: To successfull complete this section, ou need to understand: Identif collinear points. The order of operations (1.) Graph the line
More informationApplication 2.4 Implementing Euler's Method
Application 2.4 Implementing Euler's Method One's understanding of a numerical algorithm is sharpened by considering its implementation in the form of a calculator or computer program. Figure 2.4.13 in
More informationPiecewise 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 informationMaster Thesis. Comparison and Evaluation of Didactic Methods in Numerical Analysis for the Teaching of Cubic Spline Interpolation
Master Thesis Comparison and Evaluation of Didactic Methods in Numerical Analysis for the Teaching of Cubic Spline Interpolation Abtihal Jaber Chitheer supervised by Prof. Dr. Carmen Arévalo May 17, 2017
More informationSlide 1 / 96. Linear Relations and Functions
Slide 1 / 96 Linear Relations and Functions Slide 2 / 96 Scatter Plots Table of Contents Step, Absolute Value, Piecewise, Identity, and Constant Functions Graphing Inequalities Slide 3 / 96 Scatter Plots
More information10.7. Polar Coordinates. Introduction. What you should learn. Why you should learn it. Example 1. Plotting Points on the Polar Coordinate System
_7.qxd /8/5 9: AM Page 779 Section.7 Polar Coordinates 779.7 Polar Coordinates What ou should learn Plot points on the polar coordinate sstem. Convert points from rectangular to polar form and vice versa.
More informationSurface Modeling. Polygon Tables. Types: Generating models: Polygon Surfaces. Polygon surfaces Curved surfaces Volumes. Interactive Procedural
Surface Modeling Types: Polygon surfaces Curved surfaces Volumes Generating models: Interactive Procedural Polygon Tables We specify a polygon surface with a set of vertex coordinates and associated attribute
More information0.6 Graphing Transcendental Functions
0.6 Graphing Transcendental Functions There are some special functions we need to be able to graph easily. Directions follow for exponential functions (see page 68), logarithmic functions (see page 71),
More informationChapter 19 Interpolation
19.1 One-Dimensional Interpolation Chapter 19 Interpolation Empirical data obtained experimentally often times conforms to a fixed (deterministic) but unkown functional relationship. When estimates of
More informationSplines, or: Connecting the Dots. Jens Ogniewski Information Coding Group
Splines, or: Connecting the Dots Jens Ogniewski Information Coding Group Note that not all is covered in the book, especially Change of Interpolation Centripetal Catmull-Rom and other advanced parameterization
More informationConvergence of C 2 Deficient Quartic Spline Interpolation
Advances in Computational Sciences and Technology ISSN 0973-6107 Volume 10, Number 4 (2017) pp. 519-527 Research India Publications http://www.ripublication.com Convergence of C 2 Deficient Quartic Spline
More informationIt s Not Complex Just Its Solutions Are Complex!
It s Not Comple Just Its Solutions Are Comple! Solving Quadratics with Comple Solutions 15.5 Learning Goals In this lesson, ou will: Calculate comple roots of quadratic equations and comple zeros of quadratic
More informationComposite Bezier Curves. Jim Armstrong Singularity November 2006
TechNote TN-06-006 Composite Bezier Curves Jim Armstrong Singularit November 006 This is the tenth in a series of TechNotes on the subject of applied curve mathematics in Adobe Flash TM. Each TechNote
More informationThree-Dimensional Coordinates
CHAPTER Three-Dimensional Coordinates Three-dimensional movies superimpose two slightl different images, letting viewers with polaried eeglasses perceive depth (the third dimension) on a two-dimensional
More information