Fixed-Point Iteration

Size: px
Start display at page:

Download "Fixed-Point Iteration"

Transcription

1 Fixed-Point Iteration MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Fall 2013

2 Motivation Several root-finding algorithms operate by repeatedly evaluating a function until its value does not change (or changes by a suitably small amount).

3 Motivation Several root-finding algorithms operate by repeatedly evaluating a function until its value does not change (or changes by a suitably small amount). Definition A fixed-point for a function f is a number p such that f (p) = p.

4 Equivalence The process of root-finding and the process of finding fixed points are equivalent in the following sense. Suppose g(x) is a function with a root at x = p, then f (x) = g(x) + x has a fixed point at x = p. Suppose f (x) is a function with a fixed point at x = p, then g(x) = x f (x) has a root at x = p.

5 Examples Find the fixed points (if any) of the following functions. f (x) = x f (x) = 2x f (x) = x sin πx

6 Graphical Interpretation x 1 2

7 Existence and Uniqueness Theorem (Brouwer) Suppose g C[a, b] and g(x) [a, b] for all x [a, b]. Then 1 g has a fixed point in [a, b] (existence), and 2 if, in addition, g (x) exists on (a, b) and if there exists a constant 0 < k < 1 such that g (x) k, for all x (a, b), then there is exactly one fixed point in [a, b] (uniqueness).

8 Graphical Interpretation b p g p a a x Note: g(a) a and g(b) b. If g(a) = a or if g(b) = b then g has a fixed point in [a, b].

9 Proof (1 of 2) Suppose g(a) > a and g(b) < b. Define h(x) = g(x) x. The function h C[a, b]. h(b) < 0 < h(a) so by the Intermediate Value Theorem there exists p (a, b) such that h(p) = 0 0 = h(p) g(p) = p = g(p) p

10 Proof (2 of 2) Now suppose g (x) exists on (a, b) and there exists a constant 0 < k < 1 such that g (x) k for all x (a, b).

11 Proof (2 of 2) Now suppose g (x) exists on (a, b) and there exists a constant 0 < k < 1 such that g (x) k for all x (a, b). For the purposes of contradiction suppose g has two fixed points p and q with p q.

12 Proof (2 of 2) Now suppose g (x) exists on (a, b) and there exists a constant 0 < k < 1 such that g (x) k for all x (a, b). For the purposes of contradiction suppose g has two fixed points p and q with p q. According to the Mean Value Theorem there exists a < c < b for which g(p) g(q) p q = p q p q = 1 = g (c). This contradicts the assumption that g (x) k < 1 for all x (a, b).

13 Example Show that g(x) = 2 x has a unique fixed point on [0, 1].

14 Example Show that g(x) = 2 x has a unique fixed point on [0, 1]. g C[0, 1] and g (x) = (ln 2)2 x < 0 which implies g is monotone decreasing. g(0) = 1 and g(1) = 1/2 > 0. Since g is decreasing then g(x) [0, 1] for all x [0, 1]. By the first conclusion of the Brouwer Theorem, g has a fixed point in [0, 1].

15 Example Show that g(x) = 2 x has a unique fixed point on [0, 1]. g C[0, 1] and g (x) = (ln 2)2 x < 0 which implies g is monotone decreasing. g(0) = 1 and g(1) = 1/2 > 0. Since g is decreasing then g(x) [0, 1] for all x [0, 1]. By the first conclusion of the Brouwer Theorem, g has a fixed point in [0, 1]. g (x) = (ln 2)2 x ln 2 < 1 for x (0, 1). By the second conclusion of the Brouwer Theorem, the fixed point is unique.

16 Estimating the Fixed Point (1 of 2) Let p be the unknown fixed point of g(x) = 2 x and suppose ˆp is an approximation to p. g(p) g(ˆp) p ˆp = g (y) (for some y between p and ˆp)

17 Estimating the Fixed Point (1 of 2) Let p be the unknown fixed point of g(x) = 2 x and suppose ˆp is an approximation to p. g(p) g(ˆp) = g (y) (for some y between p and ˆp) p ˆp g(p) g(ˆp) = g (y) p ˆp p 2 ˆp = (ln 2)2 y p ˆp }{{} <1

18 Estimating the Fixed Point (1 of 2) Let p be the unknown fixed point of g(x) = 2 x and suppose ˆp is an approximation to p. g(p) g(ˆp) = g (y) (for some y between p and ˆp) p ˆp g(p) g(ˆp) = g (y) p ˆp p 2 ˆp = (ln 2)2 y p ˆp }{{} <1 p 2 ˆp < p ˆp

19 Estimating the Fixed Point (1 of 2) Let p be the unknown fixed point of g(x) = 2 x and suppose ˆp is an approximation to p. g(p) g(ˆp) = g (y) (for some y between p and ˆp) p ˆp g(p) g(ˆp) = g (y) p ˆp p 2 ˆp = (ln 2)2 y p ˆp }{{} <1 p 2 ˆp < p ˆp Conclusion: 2 ˆp is a better approximation to p than ˆp was.

20 Estimating the Fixed Point (2 of 2) Let g(x) = 2 x and let x 0 = 1/2. Given x n 1 then define x n = g(x n 1 ). n x n g(x n )

21 Cobweb Diagram x

22 Fixed-Point Iteration Given g(x): INPUT p 0, tolerance ɛ, maximum iterations N STEP 1 Set i = 1. STEP 2 While i N do STEPS 3 6. STEP 3 Set p = g(p 0 ). STEP 4 If p p 0 < ɛ then OUTPUT p; STOP. STEP 5 Set i = i + 1. STEP 6 Set p 0 = p. STEP 7 OUTPUT The method failed after N iterations. ; STOP.

23 Example (1 of 2) Approximate a solution to x 3 x 1 = 0 on [1, 2] using fixed point iteration.

24 Example (1 of 2) Approximate a solution to x 3 x 1 = 0 on [1, 2] using fixed point iteration. If we let g(x) = x 3 1 then finding a fixed point of g is equivalent to finding a root of the original equation.

25 Example (1 of 2) Approximate a solution to x 3 x 1 = 0 on [1, 2] using fixed point iteration. If we let g(x) = x 3 1 then finding a fixed point of g is equivalent to finding a root of the original equation. However; g(x) maps the interval [1, 2] to the interval [1, 7].

26 Example (1 of 2) Approximate a solution to x 3 x 1 = 0 on [1, 2] using fixed point iteration. If we let g(x) = x 3 1 then finding a fixed point of g is equivalent to finding a root of the original equation. However; g(x) maps the interval [1, 2] to the interval [1, 7]. Can you find another function g which maps [1, 2] into itself?

27 Example (2 of 2) x 3 x 1 = 0 x 3 = x + 1 x = 3 x + 1 = g(x) Function g maps [1, 2] into [1, 2]. Starting with p 0 = 1 the sequence of approximations to the fixed point is {1.0, , , , , , }

28 Fixed-Point Theorem Theorem (Fixed-Point) Suppose g C[a, b] and g(x) [a, b] for all x [a, b]. Furthermore suppose that g exists on (a, b) and that there exists a constant 0 < k < 1 such that g (x) k, for x [a, b]. Then for any p 0 [a, b] the sequence defined by p n = g(p n 1 ), for n 1 converges to the unique fixed point p in [a, b].

29 Proof (1 of 2) According to Brouwer s Theorem the unique fixed point p exists in [a, b]. The sequence {p n } n=0 has the property that p n [a, b] for all n. By the MVT g(p 0 ) g(p) p 0 p = g (ξ 0 ) (with ξ 0 [a, b]) p 1 p = g (ξ 0 ) p0 p p 1 p k p 0 p.

30 Proof (2 of 2) Suppose p n p k n p 0 p for some n 1. By the MVT g(p n ) g(p) p n p = g (ξ n ) (with ξ n [a, b]) p n+1 p = g (ξ n ) p n p p n+1 p k p n p p n+1 p k n+1 p 0 p. Since 0 < k < 1, the lim n p n p = 0.

31 Error Estimate While the Fixed-Point Theorem justifies that the algorithm will converge to a fixed-point/solution of the function/equation, it does not tell us anything directly about the error present in each stage of the algorithm.

32 Error Estimate While the Fixed-Point Theorem justifies that the algorithm will converge to a fixed-point/solution of the function/equation, it does not tell us anything directly about the error present in each stage of the algorithm. Corollary If g satisfies the hypotheses of the Fixed-Point Theorem, then bounds for the error involved in using p n to approximate p are p n p k n max{p 0 a, b p 0 } and p n p k n 1 k p 1 p, for n 1.

33 Proof (1 of 2) According to the Fixed-Point Theorem p n p k n p 0 p k n max{p 0 a, b p 0 }.

34 Proof (1 of 2) According to the Fixed-Point Theorem p n p k n p 0 p k n max{p 0 a, b p 0 }. Using the MVT again we see that p n+1 p n = g(p n ) g(p n 1 ) k p n p n 1 k 2 p n 1 p n 2. k n p 1 p 0.

35 Proof (2 of 2) Assume 1 n < m then p m p n = p m p m 1 + p m 1 + p n+1 p n p m p m 1 + p m 1 p m p n+1 p n k m 1 p 1 p 0 + k m 2 p 1 p k n p 1 p 0 = k n (1 + k + k k m n 1 ) p 1 p 0 ( ) k n k i p 1 p 0 = i=0 k n 1 k p 1 p 0

36 Example Consider the equation x 3 + 4x 2 10 = 0. Develop a fixed point function to approximate a solution to this equation on the interval [1, 2]. Determine the number of iterations necessary to estimate the solution to within Estimate the solution.

37 Solution Among other possibilities: 0 = x 3 + 4x 2 10 x 2 (x + 4) = x = x + 4 = g(x).

38 Solution Among other possibilities: 0 = x 3 + 4x 2 10 x 2 (x + 4) = x = x + 4 = g(x). Upon taking the derivative of g(x) we see that on [1, 2], g (x) = 5 10(x + 4) 3/2 5 < = k. 10 (5) 3/2 If p 0 = 1 then p 1 = 2 and k n p p n 1 k p 1 p 0 = n < 10 6 n 7

39 Solution Among other possibilities: 0 = x 3 + 4x 2 10 x 2 (x + 4) = x = x + 4 = g(x). Upon taking the derivative of g(x) we see that on [1, 2], g (x) = 5 10(x + 4) 3/2 5 < = k. 10 (5) 3/2 If p 0 = 1 then p 1 = 2 and k n p p n 1 k p 1 p 0 = n < 10 6 n 7 p

40 Challenge For a given equation f (x) = 0, find a fixed point function which satisfies the conditions of the Fixed-Point Theorem.

41 Homework Read Section 2.2. Exercises: 1, 2, 3, 7, 13, 16, 23

Accelerating Convergence

Accelerating Convergence Accelerating Convergence MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Fall 2013 Motivation We have seen that most fixed-point methods for root finding converge only linearly

More information

Continuity. MATH 161 Calculus I. J. Robert Buchanan. Fall Department of Mathematics

Continuity. MATH 161 Calculus I. J. Robert Buchanan. Fall Department of Mathematics Continuity MATH 161 Calculus I J. Robert Buchanan Department of Mathematics Fall 2017 Intuitive Idea A process or an item can be described as continuous if it exists without interruption. The mathematical

More information

Mean Value Theorem. MATH 161 Calculus I. J. Robert Buchanan. Summer Department of Mathematics

Mean Value Theorem. MATH 161 Calculus I. J. Robert Buchanan. Summer Department of Mathematics Mean Value Theorem MATH 161 Calculus I J. Robert Buchanan Department of Mathematics Summer 2018 Background: Corollary to the Intermediate Value Theorem Corollary Suppose f is continuous on the closed interval

More information

Review of Power Series

Review of Power Series Review of Power Series MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Introduction In addition to the techniques we have studied so far, we may use power

More information

Mean Value Theorem. MATH 161 Calculus I. J. Robert Buchanan. Summer Department of Mathematics

Mean Value Theorem. MATH 161 Calculus I. J. Robert Buchanan. Summer Department of Mathematics Mean Value Theorem MATH 161 Calculus I J. Robert Buchanan Department of Mathematics Summer 2018 Background: Corollary to the Intermediate Value Theorem Corollary Suppose f is continuous on the closed interval

More information

6.2 Deeper Properties of Continuous Functions

6.2 Deeper Properties of Continuous Functions 6.2. DEEPER PROPERTIES OF CONTINUOUS FUNCTIONS 69 6.2 Deeper Properties of Continuous Functions 6.2. Intermediate Value Theorem and Consequences When one studies a function, one is usually interested in

More information

Solutions of Equations in One Variable. Newton s Method

Solutions of Equations in One Variable. Newton s Method Solutions of Equations in One Variable Newton s Method Numerical Analysis (9th Edition) R L Burden & J D Faires Beamer Presentation Slides prepared by John Carroll Dublin City University c 2011 Brooks/Cole,

More information

ROOT FINDING REVIEW MICHELLE FENG

ROOT FINDING REVIEW MICHELLE FENG ROOT FINDING REVIEW MICHELLE FENG 1.1. Bisection Method. 1. Root Finding Methods (1) Very naive approach based on the Intermediate Value Theorem (2) You need to be looking in an interval with only one

More information

4. We accept without proofs that the following functions are differentiable: (e x ) = e x, sin x = cos x, cos x = sin x, log (x) = 1 sin x

4. We accept without proofs that the following functions are differentiable: (e x ) = e x, sin x = cos x, cos x = sin x, log (x) = 1 sin x 4 We accept without proofs that the following functions are differentiable: (e x ) = e x, sin x = cos x, cos x = sin x, log (x) = 1 sin x x, x > 0 Since tan x = cos x, from the quotient rule, tan x = sin

More information

5.5 Deeper Properties of Continuous Functions

5.5 Deeper Properties of Continuous Functions 5.5. DEEPER PROPERTIES OF CONTINUOUS FUNCTIONS 195 5.5 Deeper Properties of Continuous Functions 5.5.1 Intermediate Value Theorem and Consequences When one studies a function, one is usually interested

More information

Section 4.2: The Mean Value Theorem

Section 4.2: The Mean Value Theorem Section 4.2: The Mean Value Theorem Before we continue with the problem of describing graphs using calculus we shall briefly pause to examine some interesting applications of the derivative. In previous

More information

Continuity. Chapter 4

Continuity. Chapter 4 Chapter 4 Continuity Throughout this chapter D is a nonempty subset of the real numbers. We recall the definition of a function. Definition 4.1. A function from D into R, denoted f : D R, is a subset of

More information

Fundamental Theorem of Calculus

Fundamental Theorem of Calculus Fundamental Theorem of Calculus MATH 6 Calculus I J. Robert Buchanan Department of Mathematics Summer 208 Remarks The Fundamental Theorem of Calculus (FTC) will make the evaluation of definite integrals

More information

PART I Lecture Notes on Numerical Solution of Root Finding Problems MATH 435

PART I Lecture Notes on Numerical Solution of Root Finding Problems MATH 435 PART I Lecture Notes on Numerical Solution of Root Finding Problems MATH 435 Professor Biswa Nath Datta Department of Mathematical Sciences Northern Illinois University DeKalb, IL. 60115 USA E mail: dattab@math.niu.edu

More information

MATH115. Sequences and Infinite Series. Paolo Lorenzo Bautista. June 29, De La Salle University. PLBautista (DLSU) MATH115 June 29, / 16

MATH115. Sequences and Infinite Series. Paolo Lorenzo Bautista. June 29, De La Salle University. PLBautista (DLSU) MATH115 June 29, / 16 MATH115 Sequences and Infinite Series Paolo Lorenzo Bautista De La Salle University June 29, 2014 PLBautista (DLSU) MATH115 June 29, 2014 1 / 16 Definition A sequence function is a function whose domain

More information

Chapter 8: Taylor s theorem and L Hospital s rule

Chapter 8: Taylor s theorem and L Hospital s rule Chapter 8: Taylor s theorem and L Hospital s rule Theorem: [Inverse Mapping Theorem] Suppose that a < b and f : [a, b] R. Given that f (x) > 0 for all x (a, b) then f 1 is differentiable on (f(a), f(b))

More information

MATH115. Indeterminate Forms and Improper Integrals. Paolo Lorenzo Bautista. June 24, De La Salle University

MATH115. Indeterminate Forms and Improper Integrals. Paolo Lorenzo Bautista. June 24, De La Salle University MATH115 Indeterminate Forms and Improper Integrals Paolo Lorenzo Bautista De La Salle University June 24, 2014 PLBautista (DLSU) MATH115 June 24, 2014 1 / 25 Theorem (Mean-Value Theorem) Let f be a function

More information

Thus f is continuous at x 0. Matthew Straughn Math 402 Homework 6

Thus f is continuous at x 0. Matthew Straughn Math 402 Homework 6 Matthew Straughn Math 402 Homework 6 Homework 6 (p. 452) 14.3.3, 14.3.4, 14.3.5, 14.3.8 (p. 455) 14.4.3* (p. 458) 14.5.3 (p. 460) 14.6.1 (p. 472) 14.7.2* Lemma 1. If (f (n) ) converges uniformly to some

More information

Limit Theorems. MATH 464/506, Real Analysis. J. Robert Buchanan. Summer Department of Mathematics. J. Robert Buchanan Limit Theorems

Limit Theorems. MATH 464/506, Real Analysis. J. Robert Buchanan. Summer Department of Mathematics. J. Robert Buchanan Limit Theorems Limit s MATH 464/506, Real Analysis J. Robert Buchanan Department of Mathematics Summer 2007 Bounded Functions Definition Let A R, let f : A R, and let c R be a cluster point of A. We say that f is bounded

More information

Taylor and Maclaurin Series

Taylor and Maclaurin Series Taylor and Maclaurin Series MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Background We have seen that some power series converge. When they do, we can think of them as

More information

Bisection Method. and compute f (p 1 ). repeat with p 2 = a 2+b 2

Bisection Method. and compute f (p 1 ). repeat with p 2 = a 2+b 2 Bisection Method Given continuous function f (x) on the interval [a, b] with f (a) f (b) < 0, there must be a root in (a, b). To find a root: set [a 1, b 1 ] = [a, b]. set p 1 = a 1+b 1 2 and compute f

More information

Variable. Peter W. White Fall 2018 / Numerical Analysis. Department of Mathematics Tarleton State University

Variable. Peter W. White Fall 2018 / Numerical Analysis. Department of Mathematics Tarleton State University Newton s Iterative s Peter W. White white@tarleton.edu Department of Mathematics Tarleton State University Fall 2018 / Numerical Analysis Overview Newton s Iterative s Newton s Iterative s Newton s Iterative

More information

Riemann Integrable Functions

Riemann Integrable Functions Riemann Integrable Functions MATH 464/506, Real Analysis J. Robert Buchanan Department of Mathematics Summer 2007 Cauchy Criterion Theorem (Cauchy Criterion) A function f : [a, b] R belongs to R[a, b]

More information

Math 104: Homework 7 solutions

Math 104: Homework 7 solutions Math 04: Homework 7 solutions. (a) The derivative of f () = is f () = 2 which is unbounded as 0. Since f () is continuous on [0, ], it is uniformly continous on this interval by Theorem 9.2. Hence for

More information

Absolute Convergence and the Ratio Test

Absolute Convergence and the Ratio Test Absolute Convergence and the Ratio Test MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Bacground Remar: All previously covered tests for convergence/divergence apply only

More information

Advanced Calculus I Chapter 2 & 3 Homework Solutions October 30, Prove that f has a limit at 2 and x + 2 find it. f(x) = 2x2 + 3x 2 x + 2

Advanced Calculus I Chapter 2 & 3 Homework Solutions October 30, Prove that f has a limit at 2 and x + 2 find it. f(x) = 2x2 + 3x 2 x + 2 Advanced Calculus I Chapter 2 & 3 Homework Solutions October 30, 2009 2. Define f : ( 2, 0) R by f(x) = 2x2 + 3x 2. Prove that f has a limit at 2 and x + 2 find it. Note that when x 2 we have f(x) = 2x2

More information

Neville s Method. MATH 375 Numerical Analysis. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Neville s Method

Neville s Method. MATH 375 Numerical Analysis. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Neville s Method Neville s Method MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Fall 2013 Motivation We have learned how to approximate a function using Lagrange polynomials and how to estimate

More information

Interpolation and the Lagrange Polynomial

Interpolation and the Lagrange Polynomial Interpolation and the Lagrange Polynomial MATH 375 J. Robert Buchanan Department of Mathematics Fall 2013 Introduction We often choose polynomials to approximate other classes of functions. Theorem (Weierstrass

More information

Separable Differential Equations

Separable Differential Equations Separable Differential Equations MATH 6 Calculus I J. Robert Buchanan Department of Mathematics Fall 207 Background We have previously solved differential equations of the forms: y (t) = k y(t) (exponential

More information

HOMEWORK ASSIGNMENT 5

HOMEWORK ASSIGNMENT 5 HOMEWORK ASSIGNMENT 5 DUE 1 MARCH, 2016 1) Let f(x) = 1 if x is rational and f(x) = 0 if x is irrational. Show that f is not continuous at any real number. Solution Fix any x R. We will show that f is

More information

MAT137 Calculus! Lecture 10

MAT137 Calculus! Lecture 10 MAT137 Calculus! Lecture 10 Today we will study the Mean Value Theorem and its applications. Extrema. Optimization Problems. (4.2-4.5) PS4 is due this Friday June 23. Next class: Curve Sketching (4.6-4.8)

More information

The definition, and some continuity laws. Types of discontinuities. The Squeeze Theorem. Two special limits. The IVT and EVT.

The definition, and some continuity laws. Types of discontinuities. The Squeeze Theorem. Two special limits. The IVT and EVT. MAT137 - Week 5 The deadline to drop to MAT135 is tomorrow. (Details on course website.) The deadline to let us know you have a scheduling conflict with Test 1 is also tomorrow. (Details on the course

More information

MATH 2053 Calculus I Review for the Final Exam

MATH 2053 Calculus I Review for the Final Exam MATH 05 Calculus I Review for the Final Exam (x+ x) 9 x 9 1. Find the limit: lim x 0. x. Find the limit: lim x + x x (x ).. Find lim x (x 5) = L, find such that f(x) L < 0.01 whenever 0 < x

More information

5.5 Deeper Properties of Continuous Functions

5.5 Deeper Properties of Continuous Functions 200 CHAPTER 5. LIMIT AND CONTINUITY OF A FUNCTION 5.5 Deeper Properties of Continuous Functions 5.5.1 Intermediate Value Theorem and Consequences When one studies a function, one is usually interested

More information

Math 421, Homework #9 Solutions

Math 421, Homework #9 Solutions Math 41, Homework #9 Solutions (1) (a) A set E R n is said to be path connected if for any pair of points x E and y E there exists a continuous function γ : [0, 1] R n satisfying γ(0) = x, γ(1) = y, and

More information

MATH 409 Advanced Calculus I Lecture 16: Mean value theorem. Taylor s formula.

MATH 409 Advanced Calculus I Lecture 16: Mean value theorem. Taylor s formula. MATH 409 Advanced Calculus I Lecture 16: Mean value theorem. Taylor s formula. Points of local extremum Let f : E R be a function defined on a set E R. Definition. We say that f attains a local maximum

More information

Hence, (f(x) f(x 0 )) 2 + (g(x) g(x 0 )) 2 < ɛ

Hence, (f(x) f(x 0 )) 2 + (g(x) g(x 0 )) 2 < ɛ Matthew Straughn Math 402 Homework 5 Homework 5 (p. 429) 13.3.5, 13.3.6 (p. 432) 13.4.1, 13.4.2, 13.4.7*, 13.4.9 (p. 448-449) 14.2.1, 14.2.2 Exercise 13.3.5. Let (X, d X ) be a metric space, and let f

More information

f ', the first derivative of a differentiable function, f. Use the

f ', the first derivative of a differentiable function, f. Use the f, f ', and The graph given to the right is the graph of graph to answer the questions below. f '' Relationships and The Extreme Value Theorem 1. On the interval [0, 8], are there any values where f(x)

More information

Lecture 10: Finite Differences for ODEs & Nonlinear Equations

Lecture 10: Finite Differences for ODEs & Nonlinear Equations Lecture 10: Finite Differences for ODEs & Nonlinear Equations J.K. Ryan@tudelft.nl WI3097TU Delft Institute of Applied Mathematics Delft University of Technology 21 November 2012 () Finite Differences

More information

Student Study Session. Theorems

Student Study Session. Theorems Students should be able to apply and have a geometric understanding of the following: Intermediate Value Theorem Mean Value Theorem for derivatives Extreme Value Theorem Name Formal Statement Restatement

More information

Absolute Convergence and the Ratio Test

Absolute Convergence and the Ratio Test Absolute Convergence and the Ratio Test MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Bacground Remar: All previously covered tests for convergence/divergence apply only

More information

Section 8.7. Taylor and MacLaurin Series. (1) Definitions, (2) Common Maclaurin Series, (3) Taylor Polynomials, (4) Applications.

Section 8.7. Taylor and MacLaurin Series. (1) Definitions, (2) Common Maclaurin Series, (3) Taylor Polynomials, (4) Applications. Section 8.7 Taylor and MacLaurin Series (1) Definitions, (2) Common Maclaurin Series, (3) Taylor Polynomials, (4) Applications. MATH 126 (Section 8.7) Taylor and MacLaurin Series The University of Kansas

More information

Geometric Series and the Ratio and Root Test

Geometric Series and the Ratio and Root Test Geometric Series and the Ratio and Root Test James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 5, 2018 Outline 1 Geometric Series

More information

Linear Independence. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics

Linear Independence. MATH 322, Linear Algebra I. J. Robert Buchanan. Spring Department of Mathematics Linear Independence MATH 322, Linear Algebra I J. Robert Buchanan Department of Mathematics Spring 2015 Introduction Given a set of vectors {v 1, v 2,..., v r } and another vector v span{v 1, v 2,...,

More information

Section 10.7 Taylor series

Section 10.7 Taylor series Section 10.7 Taylor series 1. Common Maclaurin series 2. s and approximations with Taylor polynomials 3. Multiplication and division of power series Math 126 Enhanced 10.7 Taylor Series The University

More information

Bessel s Equation. MATH 365 Ordinary Differential Equations. J. Robert Buchanan. Fall Department of Mathematics

Bessel s Equation. MATH 365 Ordinary Differential Equations. J. Robert Buchanan. Fall Department of Mathematics Bessel s Equation MATH 365 Ordinary Differential Equations J. Robert Buchanan Department of Mathematics Fall 2018 Background Bessel s equation of order ν has the form where ν is a constant. x 2 y + xy

More information

Arc Length and Surface Area in Parametric Equations

Arc Length and Surface Area in Parametric Equations Arc Length and Surface Area in Parametric Equations MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2011 Background We have developed definite integral formulas for arc length

More information

Math 142 Week-in-Review #4 (Sections , 4.1, and 4.2)

Math 142 Week-in-Review #4 (Sections , 4.1, and 4.2) Math 142 WIR, copyright Angie Allen, Fall 2018 1 Math 142 Week-in-Review #4 (Sections 3.1-3.3, 4.1, and 4.2) Note: This collection of questions is intended to be a brief overview of the exam material (with

More information

Fixed point iteration Numerical Analysis Math 465/565

Fixed point iteration Numerical Analysis Math 465/565 Fixed point iteration Numerical Analysis Math 465/565 1 Fixed Point Iteration Suppose we wanted to solve : f(x) = cos(x) x =0 or cos(x) =x We might consider a iteration of this type : x k+1 = cos(x k )

More information

Chain Rule. MATH 311, Calculus III. J. Robert Buchanan. Spring Department of Mathematics

Chain Rule. MATH 311, Calculus III. J. Robert Buchanan. Spring Department of Mathematics 3.33pt Chain Rule MATH 311, Calculus III J. Robert Buchanan Department of Mathematics Spring 2019 Single Variable Chain Rule Suppose y = g(x) and z = f (y) then dz dx = d (f (g(x))) dx = f (g(x))g (x)

More information

Discrete dynamics on the real line

Discrete dynamics on the real line Chapter 2 Discrete dynamics on the real line We consider the discrete time dynamical system x n+1 = f(x n ) for a continuous map f : R R. Definitions The forward orbit of x 0 is: O + (x 0 ) = {x 0, f(x

More information

MA 8019: Numerical Analysis I Solution of Nonlinear Equations

MA 8019: Numerical Analysis I Solution of Nonlinear Equations MA 8019: Numerical Analysis I Solution of Nonlinear Equations Suh-Yuh Yang ( 楊肅煜 ) Department of Mathematics, National Central University Jhongli District, Taoyuan City 32001, Taiwan syyang@math.ncu.edu.tw

More information

MAT01B1: the Mean Value Theorem

MAT01B1: the Mean Value Theorem MAT01B1: the Mean Value Theorem Dr Craig 15 August 2018 My details: acraig@uj.ac.za Consulting hours: Monday 14h40 15h25 Thursday 11h20 12h55 Friday (this week): 11h20 12h30 Office C-Ring 508 https://andrewcraigmaths.wordpress.com/

More information

Numerical Methods

Numerical Methods Numerical Methods 263-2014 Prof. M. K. Banda Botany Building: 2-10. Prof. M. K. Banda (Tuks) WTW263 Semester II 1 / 18 Topic 1: Solving Nonlinear Equations Prof. M. K. Banda (Tuks) WTW263 Semester II 2

More information

Linearization and Extreme Values of Functions

Linearization and Extreme Values of Functions Linearization and Extreme Values of Functions 3.10 Linearization and Differentials Linear or Tangent Line Approximations of function values Equation of tangent to y = f(x) at (a, f(a)): Tangent line approximation

More information

Continuity. Matt Rosenzweig

Continuity. Matt Rosenzweig Continuity Matt Rosenzweig Contents 1 Continuity 1 1.1 Rudin Chapter 4 Exercises........................................ 1 1.1.1 Exercise 1............................................. 1 1.1.2 Exercise

More information

Homework 11. Solutions

Homework 11. Solutions Homework 11. Solutions Problem 2.3.2. Let f n : R R be 1/n times the characteristic function of the interval (0, n). Show that f n 0 uniformly and f n µ L = 1. Why isn t it a counterexample to the Lebesgue

More information

BEKG 2452 NUMERICAL METHODS Solution of Nonlinear Equations

BEKG 2452 NUMERICAL METHODS Solution of Nonlinear Equations BEKG 2452 NUMERICAL METHODS Solution of Nonlinear Equations Ser Lee Loh a, Wei Sen Loi a a Fakulti Kejuruteraan Elektrik Universiti Teknikal Malaysia Melaka Lesson Outcome Upon completion of this lesson,

More information

Math 117: Honours Calculus I Fall, 2002 List of Theorems. a n k b k. k. Theorem 2.1 (Convergent Bounded) A convergent sequence is bounded.

Math 117: Honours Calculus I Fall, 2002 List of Theorems. a n k b k. k. Theorem 2.1 (Convergent Bounded) A convergent sequence is bounded. Math 117: Honours Calculus I Fall, 2002 List of Theorems Theorem 1.1 (Binomial Theorem) For all n N, (a + b) n = n k=0 ( ) n a n k b k. k Theorem 2.1 (Convergent Bounded) A convergent sequence is bounded.

More information

Section 4.2 The Mean Value Theorem

Section 4.2 The Mean Value Theorem Section 4.2 The Mean Value Theorem Ruipeng Shen October 2nd Ruipeng Shen MATH 1ZA3 October 2nd 1 / 11 Rolle s Theorem Theorem (Rolle s Theorem) Let f (x) be a function that satisfies: 1. f is continuous

More information

Math 112 (Calculus I) Final Exam

Math 112 (Calculus I) Final Exam Name: Student ID: Section: Instructor: Math 112 (Calculus I) Final Exam Dec 18, 7:00 p.m. Instructions: Work on scratch paper will not be graded. For questions 11 to 19, show all your work in the space

More information

Chapter 3: Root Finding. September 26, 2005

Chapter 3: Root Finding. September 26, 2005 Chapter 3: Root Finding September 26, 2005 Outline 1 Root Finding 2 3.1 The Bisection Method 3 3.2 Newton s Method: Derivation and Examples 4 3.3 How To Stop Newton s Method 5 3.4 Application: Division

More information

Continuity. Chapter 4

Continuity. Chapter 4 Chapter 4 Continuity Throughout this chapter D is a nonempty subset of the real numbers. We recall the definition of a function. Definition 4.1. A function from D into R, denoted f : D R, is a subset of

More information

The First Derivative and Second Derivative Test

The First Derivative and Second Derivative Test The First Derivative and Second Derivative Test James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University April 9, 2018 Outline 1 Extremal Values 2

More information

Computer Arithmetic. MATH 375 Numerical Analysis. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Computer Arithmetic

Computer Arithmetic. MATH 375 Numerical Analysis. J. Robert Buchanan. Fall Department of Mathematics. J. Robert Buchanan Computer Arithmetic Computer Arithmetic MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Fall 2013 Machine Numbers When performing arithmetic on a computer (laptop, desktop, mainframe, cell phone,

More information

Chapter 1. Root Finding Methods. 1.1 Bisection method

Chapter 1. Root Finding Methods. 1.1 Bisection method Chapter 1 Root Finding Methods We begin by considering numerical solutions to the problem f(x) = 0 (1.1) Although the problem above is simple to state it is not always easy to solve analytically. This

More information

Homework #12 corrections

Homework #12 corrections Homework #2 corrections April 25, 205 (284) Let f() = 2 sin for 0 and f(0) = 0 (a) Use Theorems 283 and 284 to show f is differentiable at each a 0 and calculate f (a) Use, without proof, the fact that

More information

The First Derivative and Second Derivative Test

The First Derivative and Second Derivative Test The First Derivative and Second Derivative Test James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University November 8, 2017 Outline Extremal Values The

More information

Fundamental Trigonometric Identities

Fundamental Trigonometric Identities Fundamental Trigonometric Identities MATH 160, Precalculus J. Robert Buchanan Department of Mathematics Fall 2011 Objectives In this lesson we will learn to: recognize and write the fundamental trigonometric

More information

Solutions to Math 41 First Exam October 18, 2012

Solutions to Math 41 First Exam October 18, 2012 Solutions to Math 4 First Exam October 8, 202. (2 points) Find each of the following its, with justification. If the it does not exist, explain why. If there is an infinite it, then explain whether it

More information

Math 473: Practice Problems for Test 1, Fall 2011, SOLUTIONS

Math 473: Practice Problems for Test 1, Fall 2011, SOLUTIONS Math 473: Practice Problems for Test 1, Fall 011, SOLUTIONS Show your work: 1. (a) Compute the Taylor polynomials P n (x) for f(x) = sin x and x 0 = 0. Solution: Compute f(x) = sin x, f (x) = cos x, f

More information

Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 7 Solutions Please write neatly, and in complete sentences when possible.

Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 7 Solutions Please write neatly, and in complete sentences when possible. Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 7 Solutions Please write neatly, and in complete sentences when possible. Do the following problems from the book: 4.2.1, 4.2.3, 4.2.6, 4.2.8,

More information

MAT01B1: the Mean Value Theorem

MAT01B1: the Mean Value Theorem MAT01B1: the Mean Value Theorem Dr Craig 21 August 2017 My details: acraig@uj.ac.za Consulting hours: Monday 14h40 15h25 Thursday 09h40 11h15 Friday (this week): 11h20 12h30 14h00 16h00 Office C-Ring 508

More information

Differentiation - Important Theorems

Differentiation - Important Theorems Differentiation - Important Theorems Philippe B Laval KSU Spring 2012 Philippe B Laval (KSU) Differentiation - Important Theorems Spring 2012 1 / 10 Introduction We study several important theorems related

More information

Problems for Chapter 3.

Problems for Chapter 3. Problems for Chapter 3. Let A denote a nonempty set of reals. The complement of A, denoted by A, or A C is the set of all points not in A. We say that belongs to the interior of A, Int A, if there eists

More information

PRACTICE PROBLEM SET

PRACTICE PROBLEM SET PRACTICE PROBLEM SET NOTE: On the exam, you will have to show all your work (unless told otherwise), so write down all your steps and justify them. Exercise. Solve the following inequalities: () x < 3

More information

Geometric Series and the Ratio and Root Test

Geometric Series and the Ratio and Root Test Geometric Series and the Ratio and Root Test James K. Peterson Department of Biological Sciences and Department of Mathematical Sciences Clemson University September 5, 2017 Outline Geometric Series The

More information

Limit Laws- Theorem 2.2.1

Limit Laws- Theorem 2.2.1 Limit Laws- Theorem 2.2.1 If L, M, c, and k are real numbers and lim x c f (x) =L and lim g(x) =M, then x c 1 Sum Rule: lim x c (f (x)+g(x)) = L + M 2 Difference Rule: lim x c (f (x) g(x)) = L M 3 Constant

More information

Power Series. Part 1. J. Gonzalez-Zugasti, University of Massachusetts - Lowell

Power Series. Part 1. J. Gonzalez-Zugasti, University of Massachusetts - Lowell Power Series Part 1 1 Power Series Suppose x is a variable and c k & a are constants. A power series about x = 0 is c k x k A power series about x = a is c k x a k a = center of the power series c k =

More information

Properties of Logarithms

Properties of Logarithms Properties of Logarithms MATH 160, Precalculus J. Robert Buchanan Department of Mathematics Fall 2011 Objectives In this lesson we will learn to: use the change-of-base formula to rewrite and evaluate

More information

Antiderivatives and Indefinite Integrals

Antiderivatives and Indefinite Integrals Antiderivatives and Indefinite Integrals MATH 151 Calculus for Management J. Robert Buchanan Department of Mathematics Fall 2018 Objectives After completing this lesson we will be able to use the definition

More information

Math 151a week 1 discussion notes

Math 151a week 1 discussion notes Math 151a week 1 discussion notes Jean-Michel Maldague January 1, 017 Logistics I am your TA! My name is Jean-Michel Maldague. Welcome to numerical analysis. OH: Tuesdays 11-1, Thursdays 1-1, and by appointment,

More information

Implicit Differentiation and Inverse Trigonometric Functions

Implicit Differentiation and Inverse Trigonometric Functions Implicit Differentiation an Inverse Trigonometric Functions MATH 161 Calculus I J. Robert Buchanan Department of Mathematics Summer 2018 Explicit vs. Implicit Functions 0.5 1 y 0.0 y 2 0.5 3 4 1.0 0.5

More information

Fixed Point Theorems

Fixed Point Theorems Fixed Point Theorems Definition: Let X be a set and let f : 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

Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 8 Solutions Please write neatly, and in complete sentences when possible.

Math 320: Real Analysis MWF 1pm, Campion Hall 302 Homework 8 Solutions Please write neatly, and in complete sentences when possible. Math 320: Real Analysis MWF pm, Campion Hall 302 Homework 8 Solutions Please write neatly, and in complete sentences when possible. Do the following problems from the book: 4.3.5, 4.3.7, 4.3.8, 4.3.9,

More information

MATH 4211/6211 Optimization Basics of Optimization Problems

MATH 4211/6211 Optimization Basics of Optimization Problems MATH 4211/6211 Optimization Basics of Optimization Problems Xiaojing Ye Department of Mathematics & Statistics Georgia State University Xiaojing Ye, Math & Stat, Georgia State University 0 A standard minimization

More information

Calculus and Parametric Equations

Calculus and Parametric Equations Calculus and Parametric Equations MATH 211, Calculus II J. Robert Buchanan Department of Mathematics Spring 2018 Introduction Given a pair a parametric equations x = f (t) y = g(t) for a t b we know how

More information

Romberg Integration. MATH 375 Numerical Analysis. J. Robert Buchanan. Spring Department of Mathematics

Romberg Integration. MATH 375 Numerical Analysis. J. Robert Buchanan. Spring Department of Mathematics Romberg Integration MATH 375 Numerical Analysis J. Robert Buchanan Department of Mathematics Spring 019 Objectives and Background In this lesson we will learn to obtain high accuracy approximations to

More information

Announcements. Topics: Homework:

Announcements. Topics: Homework: Topics: Announcements - section 2.6 (limits at infinity [skip Precise Definitions (middle of pg. 134 end of section)]) - sections 2.1 and 2.7 (rates of change, the derivative) - section 2.8 (the derivative

More information

Differentiation. Table of contents Definition Arithmetics Composite and inverse functions... 5

Differentiation. Table of contents Definition Arithmetics Composite and inverse functions... 5 Differentiation Table of contents. Derivatives................................................. 2.. Definition................................................ 2.2. Arithmetics...............................................

More information

Section 2.9 The Mean Value Theorem

Section 2.9 The Mean Value Theorem 1 Section 2.9 The Mean Value Theorem Rolle s Theorem:( What goes up must come down theorem ) Suppose that f is continuous on the closed interval [a, b] f is differentiable on the open interval (a, b) f(a)

More information

Math 106 Answers to Exam 1a Fall 2015

Math 106 Answers to Exam 1a Fall 2015 Math 06 Answers to Exam a Fall 05.. Find the derivative of the following functions. Do not simplify your answers. (a) f(x) = ex cos x x + (b) g(z) = [ sin(z ) + e z] 5 Using the quotient rule on f(x) and

More information

6.2 Important Theorems

6.2 Important Theorems 6.2. IMPORTANT THEOREMS 223 6.2 Important Theorems 6.2.1 Local Extrema and Fermat s Theorem Definition 6.2.1 (local extrema) Let f : I R with c I. 1. f has a local maximum at c if there is a neighborhood

More information

Math 261 Calculus I. Test 1 Study Guide. Name. Decide whether the limit exists. If it exists, find its value. 1) lim x 1. f(x) 2) lim x -1/2 f(x)

Math 261 Calculus I. Test 1 Study Guide. Name. Decide whether the limit exists. If it exists, find its value. 1) lim x 1. f(x) 2) lim x -1/2 f(x) Math 261 Calculus I Test 1 Study Guide Name Decide whether the it exists. If it exists, find its value. 1) x 1 f(x) 2) x -1/2 f(x) Complete the table and use the result to find the indicated it. 3) If

More information

Summer Jump-Start Program for Analysis, 2012 Song-Ying Li

Summer Jump-Start Program for Analysis, 2012 Song-Ying Li Summer Jump-Start Program for Analysis, 01 Song-Ying Li 1 Lecture 6: Uniformly continuity and sequence of functions 1.1 Uniform Continuity Definition 1.1 Let (X, d 1 ) and (Y, d ) are metric spaces and

More information

MATH 409 Advanced Calculus I Lecture 10: Continuity. Properties of continuous functions.

MATH 409 Advanced Calculus I Lecture 10: Continuity. Properties of continuous functions. MATH 409 Advanced Calculus I Lecture 10: Continuity. Properties of continuous functions. Continuity Definition. Given a set E R, a function f : E R, and a point c E, the function f is continuous at c if

More information

MAT137 Calculus! Lecture 9

MAT137 Calculus! Lecture 9 MAT137 Calculus! Lecture 9 Today we will study: Limits at infinity. L Hôpital s Rule. Mean Value Theorem. (11.5,11.6, 4.1) PS3 is due this Friday June 16. Next class: Applications of the Mean Value Theorem.

More information

MTAEA Differentiation

MTAEA Differentiation School of Economics, Australian National University February 5, 2010 Basic Properties of the Derivative. Secant Tangent Applet l 3 l 2 l 1 a a 3 a 2 a 1 Figure: The derivative of f at a is the limiting

More information

Exercise 2. Prove that [ 1, 1] is the set of all the limit points of ( 1, 1] = {x R : 1 <

Exercise 2. Prove that [ 1, 1] is the set of all the limit points of ( 1, 1] = {x R : 1 < Math 316, Intro to Analysis Limits of functions We are experts at taking limits of sequences as the indexing parameter gets close to infinity. What about limits of functions as the independent variable

More information

(b) Write the DTDS: s t+1 =

(b) Write the DTDS: s t+1 = Math 155. Homework 4. Sections 1.9, 1.11-2.1 Do the following problems from the Adler text: 1.11: 2 (note: c = e ατ ), 6, 15, 16 2.1: 26, 28 2.2: 32, 34 Also do the following problems. 1. Three seals splash

More information