Intro to Numerical Methods

Size: px
Start display at page:

Download "Intro to Numerical Methods"

Transcription

1 COLUMBIA UNIVERSITY Intro to Numerical Methods APAM E4300 (1) MIDTERM IN-CLASS SAMPLE EXAM MARCH 11, 013 INSTRUCTOR: SANDRO FUSCO FAMILY NAME: GIVEN NAME: UNI: INSTRUCTIONS: 1. Attempt all seven (7) questions.. Your work must justify the answer you give. 3. Point values are as shown. Work is required for full credit, and may earn partial credit. 4. Be sure to indicate your answer VERY clearly. Put your answer in a circle or box when applicable. 5. No lecture notes and/or books are permitted. 6. This is the first of nine (9) pages. Question Points Marks Extra Credit 10 Total 100 APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE 1 OF 9

2 Problem 1: (10 Points) a) [ points] For a general root finding problem, list the following three algorithms in order of increasing speed (where by faster we mean takes less steps to converge to an answer): Secant method, Newton s method, Bisection method b) [ points] Write the equation for the tangent line to y = f(x) at x = p. c) [ points] Solve for the x-intercept of the line in point (b). What formula have you derived, with what roles for p and x? d) [ points] Write the equation of the line that intersects the curve y = f(x) at x = p and x = q. e) [ points] Solve for the x-intercept of the line in point (d). What formula have you derived, with what roles for p, q, and x? a) [ points]: Bisection method, Secant method, Newton s method b) [ points]: Write the equation for the tangent line to y = f(x) at x = p. y fp f px p c) [ points] Solve for the x-intercept of the line in point (b). What formula have you derived, with what roles for p and x? When y 0, x p. This is the step of Newton s method with the current iterate x k = p and the new iterate x k+1 = x. d) [ points] Write the equation of the line that intersects the curve y = f(x) at x = p and x = q. y fp fq fp x p q p e) [ points] Solve for the x-intercept of the line in point (d). What formula have you derived, with what roles for p, q, and x? When y 0, x p fp. This is the step of Secant method with x k = p, x k-1 = q and the new iterate x k+1 = x. APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE OF 9

3 Problem : (15 Points) a) [5 points] Find the n-th Taylor Polynomial approximation to expanded around x=0. (Maclaurin Series expansion) b) [5 points] Starting with 1, add terms one at the time in order to estimate e 0.5. After each new term is added, compute the true ε t and approximate ε a percent relative errors (use the true value e 0.5 = ) c) [5 points] Add new terms until the absolute value of the approximate error ε a falls below a pre-specified error criterion ε s conforming to three (3) significant figures. a) Recall that the Taylor series expansion of a function f(x) about a point x 0 is From this we can define a sequence of polynomials of increasing degree that approximate the function near the point x 0. Since all derivatives of f(x) = e x are again just e x, the Taylor polynomials from a series expansion about the point x 0 = 0 are: T 1, T 1 1!, T 1 1!!, T 1 1!! 3!, T 1 1!! 3!!. b) The first estimate is simply equal to 1. The second estimate is then given by Hence we have:!.. 100% 9.0% and.. 100%. 33.3%, and so on. c) The error criterion that ensures a result that is correct to at least three significant figures is given by the formula % 0.05%. Thus, we will add terms to the series until falls below this level. Term Result Thus, after six terms are included the approximate error falls below 0.05% and the computation is terminated. APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE 3 OF 9

4 Problem 3: (15 Points) Let n and m be positive integers and consider the binary floating point system where our machine stores numbers of the following form: 1. where 0, 1,,, and 0,1 for all k. Remember: In a binary system each a k gets multiplied by -k and all these get added up to produce the number being represented. a) [5 points] In terms of n and m, how many numbers are in this system? Don t forget the ± b) [5 points] Let m= and n=5. What is machine precision if we approximate all numbers by rounding to the closest number in the floating point system? c) [5 points] Let m=. Find the smallest value of n that will ensure that some number in the system is bigger than 1.8. a) There are x k x (m+1) = (m+1) x k+1 numbers in this system. The first is for the ±. The other terms are obvious. b) Machine precision is the smallest number ε such that 1+ ε > 1 in the system. First we have to find the smallest floating point number larger than 1. When n=5, it is = = 1+1/3. A number gets rounded up to if it is closer to it; i.e., if it is larger than the midpoint 1+1/64. Hence the machine epsilon is ε = 1/64. c) The largest number in the system is = n. When n = 1, the largest number is = 1.5 < 1.8 When n =, the largest number is = 1.75 < 1.8 When n = 3, the largest number is = + -3 = = > 1.8 Hence n=3 is the smallest value of n that will ensure that some number in the system is bigger than 1.8. APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE 4 OF 9

5 Problem 4: (15 Points) Suppose that you are given a continuous function f and numbers a < b such that f(a) and f(b) have different signs. You may ignore floating point error for the purpose of this problem, a) [10 points] Write a short MATLAB function utilizing the bisection method to find the root of f in [a,b]. The output should be [c iter] where c is within ½ x of a root of f and iter is the number of iterations (i.e., bisections) that were performed. The first line can be written as follows: % The program starts here. function [c iter] = bisect(f,a,b) b) [5 points] Suppose that b - a = 64 and note that log (10) 3.3. What is the number of iterations that the function described in part (a) should require to finish? a) See code on the course website. where delta = ½ x b) We know that: b a k 64 = 10 k Hence we can stop after k = 40 iterations. k 6 k k 10log ( 10) APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE 5 OF 9

6 Problem 5: (15 Points) a) [10 points] In class we have seen one way to approximate the derivative of a function f: for some small number h (forward finite difference). Assuming that f C, use Taylor s Theorem to determine the accuracy of this approximation. b) [5 points] Show that, with this formula, we can approximate a derivative to only about the square root of the machine precision. a) To determine the accuracy of this approximation, we use Taylor s Theorem, assuming that f C : This shows that the approximation is first-order accurate. "ξ, ξx,xh ". b) The roundoff also plays a role in the evaluation of the forward finite difference. For example, if h is so small that x+h is rounded to x, then the computed finite difference is zero. More generally, even if the only error made is in rounding the values f(x+h) and f(x), then the computed difference quotient will be: 1 1 Since each is less than the machine precision ε, this implies that the rounding error is less than or equal to Since the truncation error is proportional to h and the rounding error is proportional to 1/h, the best accuracy is achieved when the two quantities are approximately equal. Ignoring the constants, this means that Then, with the forward finite difference, we can approximate a derivative to only about the square root of the machine precision. APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE 6 OF 9

7 Problem 6: (15 Points) Below is the MATLAB m-file for a mystery function. function output = mystery( input,n,n) for j=1:n t=1:*n; t=t'/(*n); y=0; for p=1:n y=y+^(p)*rand*t.^(p-1); X(:,p)=t.^(p-1); end beta=x\y; L=@(z) z.^(0:n-1)*beta; Lout(j)=L(input); end output=mean(lout); end Answer the following questions regarding the behavior of this function. Remember: The MATLAB command rand will produce a random number that is uniformly distributed between 0 and 1, hence with mean ½. a) [10 points] What will be the value of mystery(1/5, N, n) as both N and n get large? In other words, find lim lim 1,, 5 b) [5 points] What will be the value of mystery(½, N, n) as N gets large and n stays fixed? In other words, find lim 1,, a) lim,,. Hence: lim lim 1 5,, b) lim,,. APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE 7 OF 9

8 Problem 7: (15 Points) In class we saw that Newton s method is quadratically convergent, under suitable hypotheses. Theorem: If f C, if x 0 is sufficiently close to a root x* of f, and if f (x*) 0, then Newton s Method converges to x* and ultimately the convergence rate is quadratic; that is there exists a constant C* = f (x*)/f (x*) such that: Write the proof of this Theorem. lim k xk + 1 x* = C * x x* k See page 86 of the textbook. APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE 8 OF 9

9 Extra Credit Problem: (10 Points) a) [5 points] State Horner s Method for Polynomial Evaluation. b) [5 points] Use Horner s method to find P(3) for the polynomial P(x) = x 5 6x 4 + 8x 3 +4x 40. a) See page 10 of b) See page 11 of APAM E4300 (1) MIDTERM SAMPLE EXAM PAGE 9 OF 9

Roots of Equations (Chapters 5 and 6)

Roots of Equations (Chapters 5 and 6) Roots of Equations (Chapters 5 and 6) Problem: given f() = 0, find. In general, f() can be any function. For some forms of f(), analytical solutions are available. However, for other functions, we have

More information

Nonlinear Algebraic Equations. Lectures INF2320 p. 1/88

Nonlinear Algebraic Equations. Lectures INF2320 p. 1/88 Nonlinear Algebraic Equations Lectures INF2320 p. 1/88 Lectures INF2320 p. 2/88 Nonlinear algebraic equations When solving the system u (t) = g(u), u(0) = u 0, (1) with an implicit Euler scheme we have

More information

Rolle s Theorem. q( x) = 1

Rolle s Theorem. q( x) = 1 Lecture 1 :The Mean Value Theorem We know that constant functions have derivative zero. Is it possible for a more complicated function to have derivative zero? In this section we will answer this question

More information

Zero: If P is a polynomial and if c is a number such that P (c) = 0 then c is a zero of P.

Zero: If P is a polynomial and if c is a number such that P (c) = 0 then c is a zero of P. MATH 11011 FINDING REAL ZEROS KSU OF A POLYNOMIAL Definitions: Polynomial: is a function of the form P (x) = a n x n + a n 1 x n 1 + + a x + a 1 x + a 0. The numbers a n, a n 1,..., a 1, a 0 are called

More information

Roots of equation fx are the values of x which satisfy the above expression. Also referred to as the zeros of an equation

Roots of equation fx are the values of x which satisfy the above expression. Also referred to as the zeros of an equation LECTURE 20 SOLVING FOR ROOTS OF NONLINEAR EQUATIONS Consider the equation f = 0 Roots of equation f are the values of which satisfy the above epression. Also referred to as the zeros of an equation f()

More information

Increasing for all. Convex for all. ( ) Increasing for all (remember that the log function is only defined for ). ( ) Concave for all.

Increasing for all. Convex for all. ( ) Increasing for all (remember that the log function is only defined for ). ( ) Concave for all. 1. Differentiation The first derivative of a function measures by how much changes in reaction to an infinitesimal shift in its argument. The largest the derivative (in absolute value), the faster is evolving.

More information

Lecture 13 - Basic Number Theory.

Lecture 13 - Basic Number Theory. Lecture 13 - Basic Number Theory. Boaz Barak March 22, 2010 Divisibility and primes Unless mentioned otherwise throughout this lecture all numbers are non-negative integers. We say that A divides B, denoted

More information

G.A. Pavliotis. Department of Mathematics. Imperial College London

G.A. Pavliotis. Department of Mathematics. Imperial College London EE1 MATHEMATICS NUMERICAL METHODS G.A. Pavliotis Department of Mathematics Imperial College London 1. Numerical solution of nonlinear equations (iterative processes). 2. Numerical evaluation of integrals.

More information

Zeros of Polynomial Functions

Zeros of Polynomial Functions Review: Synthetic Division Find (x 2-5x - 5x 3 + x 4 ) (5 + x). Factor Theorem Solve 2x 3-5x 2 + x + 2 =0 given that 2 is a zero of f(x) = 2x 3-5x 2 + x + 2. Zeros of Polynomial Functions Introduction

More information

Roots of Polynomials

Roots of Polynomials Roots of Polynomials (Com S 477/577 Notes) Yan-Bin Jia Sep 24, 2015 A direct corollary of the fundamental theorem of algebra is that p(x) can be factorized over the complex domain into a product a n (x

More information

CS321. Introduction to Numerical Methods

CS321. Introduction to Numerical Methods CS3 Introduction to Numerical Methods Lecture Number Representations and Errors Professor Jun Zhang Department of Computer Science University of Kentucky Lexington, KY 40506-0633 August 7, 05 Number in

More information

1 if 1 x 0 1 if 0 x 1

1 if 1 x 0 1 if 0 x 1 Chapter 3 Continuity In this chapter we begin by defining the fundamental notion of continuity for real valued functions of a single real variable. When trying to decide whether a given function is or

More information

Average rate of change

Average rate of change Average rate of change 1 1 Average rate of change A fundamental philosophical truth is that everything changes. 1 Average rate of change A fundamental philosophical truth is that everything changes. In

More information

4.3 Lagrange Approximation

4.3 Lagrange Approximation 206 CHAP. 4 INTERPOLATION AND POLYNOMIAL APPROXIMATION Lagrange Polynomial Approximation 4.3 Lagrange Approximation Interpolation means to estimate a missing function value by taking a weighted average

More information

Average rate of change of y = f(x) with respect to x as x changes from a to a + h:

Average rate of change of y = f(x) with respect to x as x changes from a to a + h: L15-1 Lecture 15: Section 3.4 Definition of the Derivative Recall the following from Lecture 14: For function y = f(x), the average rate of change of y with respect to x as x changes from a to b (on [a,

More information

Lies My Calculator and Computer Told Me

Lies My Calculator and Computer Told Me Lies My Calculator and Computer Told Me 2 LIES MY CALCULATOR AND COMPUTER TOLD ME Lies My Calculator and Computer Told Me See Section.4 for a discussion of graphing calculators and computers with graphing

More information

correct-choice plot f(x) and draw an approximate tangent line at x = a and use geometry to estimate its slope comment The choices were:

correct-choice plot f(x) and draw an approximate tangent line at x = a and use geometry to estimate its slope comment The choices were: Topic 1 2.1 mode MultipleSelection text How can we approximate the slope of the tangent line to f(x) at a point x = a? This is a Multiple selection question, so you need to check all of the answers that

More information

3.3 Real Zeros of Polynomials

3.3 Real Zeros of Polynomials 3.3 Real Zeros of Polynomials 69 3.3 Real Zeros of Polynomials In Section 3., we found that we can use synthetic division to determine if a given real number is a zero of a polynomial function. This section

More information

3.2 The Factor Theorem and The Remainder Theorem

3.2 The Factor Theorem and The Remainder Theorem 3. The Factor Theorem and The Remainder Theorem 57 3. The Factor Theorem and The Remainder Theorem Suppose we wish to find the zeros of f(x) = x 3 + 4x 5x 4. Setting f(x) = 0 results in the polynomial

More information

Numerical Matrix Analysis

Numerical Matrix Analysis Numerical Matrix Analysis Lecture Notes #10 Conditioning and / Peter Blomgren, blomgren.peter@gmail.com Department of Mathematics and Statistics Dynamical Systems Group Computational Sciences Research

More information

Algebra 1 Course Title

Algebra 1 Course Title Algebra 1 Course Title Course- wide 1. What patterns and methods are being used? Course- wide 1. Students will be adept at solving and graphing linear and quadratic equations 2. Students will be adept

More information

Section 3-3 Approximating Real Zeros of Polynomials

Section 3-3 Approximating Real Zeros of Polynomials - Approimating Real Zeros of Polynomials 9 Section - Approimating Real Zeros of Polynomials Locating Real Zeros The Bisection Method Approimating Multiple Zeros Application The methods for finding zeros

More information

Representation of functions as power series

Representation of functions as power series Representation of functions as power series Dr. Philippe B. Laval Kennesaw State University November 9, 008 Abstract This document is a summary of the theory and techniques used to represent functions

More information

Lectures 5-6: Taylor Series

Lectures 5-6: Taylor Series Math 1d Instructor: Padraic Bartlett Lectures 5-: Taylor Series Weeks 5- Caltech 213 1 Taylor Polynomials and Series As we saw in week 4, power series are remarkably nice objects to work with. In particular,

More information

Critical points of once continuously differentiable functions are important because they are the only points that can be local maxima or minima.

Critical points of once continuously differentiable functions are important because they are the only points that can be local maxima or minima. Lecture 0: Convexity and Optimization We say that if f is a once continuously differentiable function on an interval I, and x is a point in the interior of I that x is a critical point of f if f (x) =

More information

Partial Fractions. Combining fractions over a common denominator is a familiar operation from algebra:

Partial Fractions. Combining fractions over a common denominator is a familiar operation from algebra: Partial Fractions Combining fractions over a common denominator is a familiar operation from algebra: From the standpoint of integration, the left side of Equation 1 would be much easier to work with than

More information

Measures of Error: for exact x and approximation x Absolute error e = x x. Relative error r = (x x )/x.

Measures of Error: for exact x and approximation x Absolute error e = x x. Relative error r = (x x )/x. ERRORS and COMPUTER ARITHMETIC Types of Error in Numerical Calculations Initial Data Errors: from experiment, modeling, computer representation; problem dependent but need to know at beginning of calculation.

More information

1.7 Graphs of Functions

1.7 Graphs of Functions 64 Relations and Functions 1.7 Graphs of Functions In Section 1.4 we defined a function as a special type of relation; one in which each x-coordinate was matched with only one y-coordinate. We spent most

More information

CS 261 Fall 2011 Solutions to Assignment #4

CS 261 Fall 2011 Solutions to Assignment #4 CS 61 Fall 011 Solutions to Assignment #4 The following four algorithms are used to implement the bisection method, Newton s method, the secant method, and the method of false position, respectively. In

More information

Rootfinding for Nonlinear Equations

Rootfinding for Nonlinear Equations > 3. Rootfinding Rootfinding for Nonlinear Equations > 3. Rootfinding Calculating the roots of an equation is a common problem in applied mathematics. f(x) = 0 (7.1) We will explore some simple numerical

More information

CS 103X: Discrete Structures Homework Assignment 3 Solutions

CS 103X: Discrete Structures Homework Assignment 3 Solutions CS 103X: Discrete Structures Homework Assignment 3 s Exercise 1 (20 points). On well-ordering and induction: (a) Prove the induction principle from the well-ordering principle. (b) Prove the well-ordering

More information

Microeconomic Theory: Basic Math Concepts

Microeconomic Theory: Basic Math Concepts Microeconomic Theory: Basic Math Concepts Matt Van Essen University of Alabama Van Essen (U of A) Basic Math Concepts 1 / 66 Basic Math Concepts In this lecture we will review some basic mathematical concepts

More information

Review of Fundamental Mathematics

Review of Fundamental Mathematics Review of Fundamental Mathematics As explained in the Preface and in Chapter 1 of your textbook, managerial economics applies microeconomic theory to business decision making. The decision-making tools

More information

JUST THE MATHS UNIT NUMBER 1.8. ALGEBRA 8 (Polynomials) A.J.Hobson

JUST THE MATHS UNIT NUMBER 1.8. ALGEBRA 8 (Polynomials) A.J.Hobson JUST THE MATHS UNIT NUMBER 1.8 ALGEBRA 8 (Polynomials) by A.J.Hobson 1.8.1 The factor theorem 1.8.2 Application to quadratic and cubic expressions 1.8.3 Cubic equations 1.8.4 Long division of polynomials

More information

Real Roots of Univariate Polynomials with Real Coefficients

Real Roots of Univariate Polynomials with Real Coefficients Real Roots of Univariate Polynomials with Real Coefficients mostly written by Christina Hewitt March 22, 2012 1 Introduction Polynomial equations are used throughout mathematics. When solving polynomials

More information

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)!

HOMEWORK 5 SOLUTIONS. n!f n (1) lim. ln x n! + xn x. 1 = G n 1 (x). (2) k + 1 n. (n 1)! Math 7 Fall 205 HOMEWORK 5 SOLUTIONS Problem. 2008 B2 Let F 0 x = ln x. For n 0 and x > 0, let F n+ x = 0 F ntdt. Evaluate n!f n lim n ln n. By directly computing F n x for small n s, we obtain the following

More information

Taylor and Maclaurin Series

Taylor and Maclaurin Series Taylor and Maclaurin Series In the preceding section we were able to find power series representations for a certain restricted class of functions. Here we investigate more general problems: Which functions

More information

5 Numerical Differentiation

5 Numerical Differentiation D. Levy 5 Numerical Differentiation 5. Basic Concepts This chapter deals with numerical approximations of derivatives. The first questions that comes up to mind is: why do we need to approximate derivatives

More information

Thnkwell s Homeschool Precalculus Course Lesson Plan: 36 weeks

Thnkwell s Homeschool Precalculus Course Lesson Plan: 36 weeks Thnkwell s Homeschool Precalculus Course Lesson Plan: 36 weeks Welcome to Thinkwell s Homeschool Precalculus! We re thrilled that you ve decided to make us part of your homeschool curriculum. This lesson

More information

Nonlinear Algebraic Equations Example

Nonlinear Algebraic Equations Example Nonlinear Algebraic Equations Example Continuous Stirred Tank Reactor (CSTR). Look for steady state concentrations & temperature. s r (in) p,i (in) i In: N spieces with concentrations c, heat capacities

More information

A Slide Show Demonstrating Newton s Method

A Slide Show Demonstrating Newton s Method The AcroT E X Web Site, 1999 A Slide Show Demonstrating Newton s Method D. P. Story The Department of Mathematics and Computer Science The Universityof Akron, Akron, OH Now go up to the curve. Now go

More information

COMP 250 Fall 2012 lecture 2 binary representations Sept. 11, 2012

COMP 250 Fall 2012 lecture 2 binary representations Sept. 11, 2012 Binary numbers The reason humans represent numbers using decimal (the ten digits from 0,1,... 9) is that we have ten fingers. There is no other reason than that. There is nothing special otherwise about

More information

Slope and Rate of Change

Slope and Rate of Change Chapter 1 Slope and Rate of Change Chapter Summary and Goal This chapter will start with a discussion of slopes and the tangent line. This will rapidly lead to heuristic developments of limits and the

More information

Normal distribution. ) 2 /2σ. 2π σ

Normal distribution. ) 2 /2σ. 2π σ Normal distribution The normal distribution is the most widely known and used of all distributions. Because the normal distribution approximates many natural phenomena so well, it has developed into a

More information

Numerical Solution of Differential

Numerical Solution of Differential Chapter 13 Numerical Solution of Differential Equations We have considered numerical solution procedures for two kinds of equations: In chapter 10 the unknown was a real number; in chapter 6 the unknown

More information

Basics of Polynomial Theory

Basics of Polynomial Theory 3 Basics of Polynomial Theory 3.1 Polynomial Equations In geodesy and geoinformatics, most observations are related to unknowns parameters through equations of algebraic (polynomial) type. In cases where

More information

Numerical Analysis An Introduction

Numerical Analysis An Introduction Walter Gautschi Numerical Analysis An Introduction 1997 Birkhauser Boston Basel Berlin CONTENTS PREFACE xi CHAPTER 0. PROLOGUE 1 0.1. Overview 1 0.2. Numerical analysis software 3 0.3. Textbooks and monographs

More information

AN INTRODUCTION TO NUMERICAL METHODS AND ANALYSIS

AN INTRODUCTION TO NUMERICAL METHODS AND ANALYSIS AN INTRODUCTION TO NUMERICAL METHODS AND ANALYSIS Revised Edition James Epperson Mathematical Reviews BICENTENNIAL 0, 1 8 0 7 z ewiley wu 2007 r71 BICENTENNIAL WILEY-INTERSCIENCE A John Wiley & Sons, Inc.,

More information

Squaring, Cubing, and Cube Rooting

Squaring, Cubing, and Cube Rooting Squaring, Cubing, and Cube Rooting Arthur T. Benjamin Harvey Mudd College Claremont, CA 91711 benjamin@math.hmc.edu I still recall my thrill and disappointment when I read Mathematical Carnival [4], by

More information

SOLVING POLYNOMIAL EQUATIONS

SOLVING POLYNOMIAL EQUATIONS C SOLVING POLYNOMIAL EQUATIONS We will assume in this appendix that you know how to divide polynomials using long division and synthetic division. If you need to review those techniques, refer to an algebra

More information

4. Continuous Random Variables, the Pareto and Normal Distributions

4. Continuous Random Variables, the Pareto and Normal Distributions 4. Continuous Random Variables, the Pareto and Normal Distributions A continuous random variable X can take any value in a given range (e.g. height, weight, age). The distribution of a continuous random

More information

Zeros of a Polynomial Function

Zeros of a Polynomial Function Zeros of a Polynomial Function An important consequence of the Factor Theorem is that finding the zeros of a polynomial is really the same thing as factoring it into linear factors. In this section we

More information

The Steepest Descent Algorithm for Unconstrained Optimization and a Bisection Line-search Method

The Steepest Descent Algorithm for Unconstrained Optimization and a Bisection Line-search Method The Steepest Descent Algorithm for Unconstrained Optimization and a Bisection Line-search Method Robert M. Freund February, 004 004 Massachusetts Institute of Technology. 1 1 The Algorithm The problem

More information

Lecture Notes on Polynomials

Lecture Notes on Polynomials Lecture Notes on Polynomials Arne Jensen Department of Mathematical Sciences Aalborg University c 008 Introduction These lecture notes give a very short introduction to polynomials with real and complex

More information

1 Lecture: Integration of rational functions by decomposition

1 Lecture: Integration of rational functions by decomposition Lecture: Integration of rational functions by decomposition into partial fractions Recognize and integrate basic rational functions, except when the denominator is a power of an irreducible quadratic.

More information

Lecture 2. Marginal Functions, Average Functions, Elasticity, the Marginal Principle, and Constrained Optimization

Lecture 2. Marginal Functions, Average Functions, Elasticity, the Marginal Principle, and Constrained Optimization Lecture 2. Marginal Functions, Average Functions, Elasticity, the Marginal Principle, and Constrained Optimization 2.1. Introduction Suppose that an economic relationship can be described by a real-valued

More information

Notes on metric spaces

Notes on metric spaces Notes on metric spaces 1 Introduction The purpose of these notes is to quickly review some of the basic concepts from Real Analysis, Metric Spaces and some related results that will be used in this course.

More information

Name: ID: Discussion Section:

Name: ID: Discussion Section: Math 28 Midterm 3 Spring 2009 Name: ID: Discussion Section: This exam consists of 6 questions: 4 multiple choice questions worth 5 points each 2 hand-graded questions worth a total of 30 points. INSTRUCTIONS:

More information

Continued Fractions and the Euclidean Algorithm

Continued Fractions and the Euclidean Algorithm Continued Fractions and the Euclidean Algorithm Lecture notes prepared for MATH 326, Spring 997 Department of Mathematics and Statistics University at Albany William F Hammond Table of Contents Introduction

More information

Mathematics 31 Pre-calculus and Limits

Mathematics 31 Pre-calculus and Limits Mathematics 31 Pre-calculus and Limits Overview After completing this section, students will be epected to have acquired reliability and fluency in the algebraic skills of factoring, operations with radicals

More information

3.3. Solving Polynomial Equations. Introduction. Prerequisites. Learning Outcomes

3.3. Solving Polynomial Equations. Introduction. Prerequisites. Learning Outcomes Solving Polynomial Equations 3.3 Introduction Linear and quadratic equations, dealt within Sections 3.1 and 3.2, are members of a class of equations, called polynomial equations. These have the general

More information

Two Fundamental Theorems about the Definite Integral

Two Fundamental Theorems about the Definite Integral Two Fundamental Theorems about the Definite Integral These lecture notes develop the theorem Stewart calls The Fundamental Theorem of Calculus in section 5.3. The approach I use is slightly different than

More information

Geometry Unit 5: Circles Part 1 Chords, Secants, and Tangents

Geometry Unit 5: Circles Part 1 Chords, Secants, and Tangents Geometry Unit 5: Circles Part 1 Chords, Secants, and Tangents Name Chords and Circles: A chord is a segment that joins two points of the circle. A diameter is a chord that contains the center of the circle.

More information

Notes on Continuous Random Variables

Notes on Continuous Random Variables Notes on Continuous Random Variables Continuous random variables are random quantities that are measured on a continuous scale. They can usually take on any value over some interval, which distinguishes

More information

This is a square root. The number under the radical is 9. (An asterisk * means multiply.)

This is a square root. The number under the radical is 9. (An asterisk * means multiply.) Page of Review of Radical Expressions and Equations Skills involving radicals can be divided into the following groups: Evaluate square roots or higher order roots. Simplify radical expressions. Rationalize

More information

18.01 Single Variable Calculus Fall 2006

18.01 Single Variable Calculus Fall 2006 MIT OpenCourseWare http://ocw.mit.edu 8.0 Single Variable Calculus Fall 2006 For information about citing these materials or our Terms of Use, visit: http://ocw.mit.edu/terms. Unit : Derivatives A. What

More information

Solving Quadratic Equations

Solving Quadratic Equations 9.3 Solving Quadratic Equations by Using the Quadratic Formula 9.3 OBJECTIVES 1. Solve a quadratic equation by using the quadratic formula 2. Determine the nature of the solutions of a quadratic equation

More information

Zeros of Polynomial Functions

Zeros of Polynomial Functions Zeros of Polynomial Functions The Rational Zero Theorem If f (x) = a n x n + a n-1 x n-1 + + a 1 x + a 0 has integer coefficients and p/q (where p/q is reduced) is a rational zero, then p is a factor of

More information

PYTHAGOREAN TRIPLES KEITH CONRAD

PYTHAGOREAN TRIPLES KEITH CONRAD PYTHAGOREAN TRIPLES KEITH CONRAD 1. Introduction A Pythagorean triple is a triple of positive integers (a, b, c) where a + b = c. Examples include (3, 4, 5), (5, 1, 13), and (8, 15, 17). Below is an ancient

More information

www.mathsbox.org.uk ab = c a If the coefficients a,b and c are real then either α and β are real or α and β are complex conjugates

www.mathsbox.org.uk ab = c a If the coefficients a,b and c are real then either α and β are real or α and β are complex conjugates Further Pure Summary Notes. Roots of Quadratic Equations For a quadratic equation ax + bx + c = 0 with roots α and β Sum of the roots Product of roots a + b = b a ab = c a If the coefficients a,b and c

More information

Lecture 10: Distinct Degree Factoring

Lecture 10: Distinct Degree Factoring CS681 Computational Number Theory Lecture 10: Distinct Degree Factoring Instructor: Piyush P Kurur Scribe: Ramprasad Saptharishi Overview Last class we left of with a glimpse into distant degree factorization.

More information

1 The Brownian bridge construction

1 The Brownian bridge construction The Brownian bridge construction The Brownian bridge construction is a way to build a Brownian motion path by successively adding finer scale detail. This construction leads to a relatively easy proof

More information

Year 9 set 1 Mathematics notes, to accompany the 9H book.

Year 9 set 1 Mathematics notes, to accompany the 9H book. Part 1: Year 9 set 1 Mathematics notes, to accompany the 9H book. equations 1. (p.1), 1.6 (p. 44), 4.6 (p.196) sequences 3. (p.115) Pupils use the Elmwood Press Essential Maths book by David Raymer (9H

More information

Implicit Differentiation

Implicit Differentiation Revision Notes 2 Calculus 1270 Fall 2007 INSTRUCTOR: Peter Roper OFFICE: LCB 313 [EMAIL: roper@math.utah.edu] Standard Disclaimer These notes are not a complete review of the course thus far, and some

More information

1. Prove that the empty set is a subset of every set.

1. Prove that the empty set is a subset of every set. 1. Prove that the empty set is a subset of every set. Basic Topology Written by Men-Gen Tsai email: b89902089@ntu.edu.tw Proof: For any element x of the empty set, x is also an element of every set since

More information

The Mean Value Theorem

The Mean Value Theorem The Mean Value Theorem THEOREM (The Extreme Value Theorem): If f is continuous on a closed interval [a, b], then f attains an absolute maximum value f(c) and an absolute minimum value f(d) at some numbers

More information

Revised Version of Chapter 23. We learned long ago how to solve linear congruences. ax c (mod m)

Revised Version of Chapter 23. We learned long ago how to solve linear congruences. ax c (mod m) Chapter 23 Squares Modulo p Revised Version of Chapter 23 We learned long ago how to solve linear congruences ax c (mod m) (see Chapter 8). It s now time to take the plunge and move on to quadratic equations.

More information

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES

MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES MASSACHUSETTS INSTITUTE OF TECHNOLOGY 6.436J/15.085J Fall 2008 Lecture 5 9/17/2008 RANDOM VARIABLES Contents 1. Random variables and measurable functions 2. Cumulative distribution functions 3. Discrete

More information

Zeros of Polynomial Functions

Zeros of Polynomial Functions Zeros of Polynomial Functions Objectives: 1.Use the Fundamental Theorem of Algebra to determine the number of zeros of polynomial functions 2.Find rational zeros of polynomial functions 3.Find conjugate

More information

CHAPTER 5 Round-off errors

CHAPTER 5 Round-off errors CHAPTER 5 Round-off errors In the two previous chapters we have seen how numbers can be represented in the binary numeral system and how this is the basis for representing numbers in computers. Since any

More information

Fixed Point Theorems

Fixed Point Theorems Fixed Point Theorems Definition: Let X be a set and let T : X X be a function that maps X into itself. (Such a function is often called an operator, a transformation, or a transform on X, and the notation

More information

FIRST YEAR CALCULUS. Chapter 7 CONTINUITY. It is a parabola, and we can draw this parabola without lifting our pencil from the paper.

FIRST YEAR CALCULUS. Chapter 7 CONTINUITY. It is a parabola, and we can draw this parabola without lifting our pencil from the paper. FIRST YEAR CALCULUS WWLCHENW L c WWWL W L Chen, 1982, 2008. 2006. This chapter originates from material used by the author at Imperial College, University of London, between 1981 and 1990. It It is is

More information

5. Factoring by the QF method

5. Factoring by the QF method 5. Factoring by the QF method 5.0 Preliminaries 5.1 The QF view of factorability 5.2 Illustration of the QF view of factorability 5.3 The QF approach to factorization 5.4 Alternative factorization by the

More information

Differentiation and Integration

Differentiation and Integration This material is a supplement to Appendix G of Stewart. You should read the appendix, except the last section on complex exponentials, before this material. Differentiation and Integration Suppose we have

More information

6 EXTENDING ALGEBRA. 6.0 Introduction. 6.1 The cubic equation. Objectives

6 EXTENDING ALGEBRA. 6.0 Introduction. 6.1 The cubic equation. Objectives 6 EXTENDING ALGEBRA Chapter 6 Extending Algebra Objectives After studying this chapter you should understand techniques whereby equations of cubic degree and higher can be solved; be able to factorise

More information

MATH 132: CALCULUS II SYLLABUS

MATH 132: CALCULUS II SYLLABUS MATH 32: CALCULUS II SYLLABUS Prerequisites: Successful completion of Math 3 (or its equivalent elsewhere). Math 27 is normally not a sufficient prerequisite for Math 32. Required Text: Calculus: Early

More information

Computer Science 281 Binary and Hexadecimal Review

Computer Science 281 Binary and Hexadecimal Review Computer Science 281 Binary and Hexadecimal Review 1 The Binary Number System Computers store everything, both instructions and data, by using many, many transistors, each of which can be in one of two

More information

0.8 Rational Expressions and Equations

0.8 Rational Expressions and Equations 96 Prerequisites 0.8 Rational Expressions and Equations We now turn our attention to rational expressions - that is, algebraic fractions - and equations which contain them. The reader is encouraged to

More information

Probability Generating Functions

Probability Generating Functions page 39 Chapter 3 Probability Generating Functions 3 Preamble: Generating Functions Generating functions are widely used in mathematics, and play an important role in probability theory Consider a sequence

More information

The Method of Least Squares. Lectures INF2320 p. 1/80

The Method of Least Squares. Lectures INF2320 p. 1/80 The Method of Least Squares Lectures INF2320 p. 1/80 Lectures INF2320 p. 2/80 The method of least squares We study the following problem: Given n points (t i,y i ) for i = 1,...,n in the (t,y)-plane. How

More information

Vector and Matrix Norms

Vector and Matrix Norms Chapter 1 Vector and Matrix Norms 11 Vector Spaces Let F be a field (such as the real numbers, R, or complex numbers, C) with elements called scalars A Vector Space, V, over the field F is a non-empty

More information

Notes on Complexity Theory Last updated: August, 2011. Lecture 1

Notes on Complexity Theory Last updated: August, 2011. Lecture 1 Notes on Complexity Theory Last updated: August, 2011 Jonathan Katz Lecture 1 1 Turing Machines I assume that most students have encountered Turing machines before. (Students who have not may want to look

More information

5.1 Derivatives and Graphs

5.1 Derivatives and Graphs 5.1 Derivatives and Graphs What does f say about f? If f (x) > 0 on an interval, then f is INCREASING on that interval. If f (x) < 0 on an interval, then f is DECREASING on that interval. A function has

More information

Section 12.6: Directional Derivatives and the Gradient Vector

Section 12.6: Directional Derivatives and the Gradient Vector Section 26: Directional Derivatives and the Gradient Vector Recall that if f is a differentiable function of x and y and z = f(x, y), then the partial derivatives f x (x, y) and f y (x, y) give the rate

More information

Course Outlines. 1. Name of the Course: Algebra I (Standard, College Prep, Honors) Course Description: ALGEBRA I STANDARD (1 Credit)

Course Outlines. 1. Name of the Course: Algebra I (Standard, College Prep, Honors) Course Description: ALGEBRA I STANDARD (1 Credit) Course Outlines 1. Name of the Course: Algebra I (Standard, College Prep, Honors) Course Description: ALGEBRA I STANDARD (1 Credit) This course will cover Algebra I concepts such as algebra as a language,

More information

Recursive Algorithms. Recursion. Motivating Example Factorial Recall the factorial function. { 1 if n = 1 n! = n (n 1)! if n > 1

Recursive Algorithms. Recursion. Motivating Example Factorial Recall the factorial function. { 1 if n = 1 n! = n (n 1)! if n > 1 Recursion Slides by Christopher M Bourke Instructor: Berthe Y Choueiry Fall 007 Computer Science & Engineering 35 Introduction to Discrete Mathematics Sections 71-7 of Rosen cse35@cseunledu Recursive Algorithms

More information

8 Polynomials Worksheet

8 Polynomials Worksheet 8 Polynomials Worksheet Concepts: Quadratic Functions The Definition of a Quadratic Function Graphs of Quadratic Functions - Parabolas Vertex Absolute Maximum or Absolute Minimum Transforming the Graph

More information

Application. Outline. 3-1 Polynomial Functions 3-2 Finding Rational Zeros of. Polynomial. 3-3 Approximating Real Zeros of.

Application. Outline. 3-1 Polynomial Functions 3-2 Finding Rational Zeros of. Polynomial. 3-3 Approximating Real Zeros of. Polynomial and Rational Functions Outline 3-1 Polynomial Functions 3-2 Finding Rational Zeros of Polynomials 3-3 Approximating Real Zeros of Polynomials 3-4 Rational Functions Chapter 3 Group Activity:

More information

63. Graph y 1 2 x and y 2 THE FACTOR THEOREM. The Factor Theorem. Consider the polynomial function. P(x) x 2 2x 15.

63. Graph y 1 2 x and y 2 THE FACTOR THEOREM. The Factor Theorem. Consider the polynomial function. P(x) x 2 2x 15. 9.4 (9-27) 517 Gear ratio d) For a fixed wheel size and chain ring, does the gear ratio increase or decrease as the number of teeth on the cog increases? decreases 100 80 60 40 20 27-in. wheel, 44 teeth

More information

This document has been written by Michaël Baudin from the Scilab Consortium. December 2010 The Scilab Consortium Digiteo. All rights reserved.

This document has been written by Michaël Baudin from the Scilab Consortium. December 2010 The Scilab Consortium Digiteo. All rights reserved. SCILAB IS NOT NAIVE This document has been written by Michaël Baudin from the Scilab Consortium. December 2010 The Scilab Consortium Digiteo. All rights reserved. December 2010 Abstract Most of the time,

More information