CISE301: Numerical Methods Topic 2: Solution of Nonlinear Equations

Similar documents
: Numerical Analysis Topic 2: Solution of Nonlinear Equations Lectures 5-11:

Lecture 2 Solution of Nonlinear Equations ( Root Finding Problems )

Numerical Methods Solution of Nonlinear Equations

Summary with Examples for Root finding Methods -Bisection -Newton Raphson -Secant

CHAPTER 4d. ROOTS OF EQUATIONS

Single Variable Optimization

Review of Taylor Series. Read Section 1.2

OPTIMISATION. Introduction Single Variable Unconstrained Optimisation Multivariable Unconstrained Optimisation Linear Programming

Root Finding

Chapter 3 Differentiation and Integration

Finite Difference Method

Chapter Newton s Method

36.1 Why is it important to be able to find roots to systems of equations? Up to this point, we have discussed how to find the solution to

Chapter 4: Root Finding

Shuai Dong. Isaac Newton. Gottfried Leibniz

EE 330 Lecture 24. Small Signal Analysis Small Signal Analysis of BJT Amplifier

Section 3.6 Complex Zeros

CIS526: Machine Learning Lecture 3 (Sept 16, 2003) Linear Regression. Preparation help: Xiaoying Huang. x 1 θ 1 output... θ M x M

Chapter 12. Ordinary Differential Equation Boundary Value (BV) Problems

Newton s Method for One - Dimensional Optimization - Theory

SOLVING NON-LINEAR SYSTEMS BY NEWTON s METHOD USING SPREADSHEET EXCEL Tay Kim Gaik Universiti Tun Hussein Onn Malaysia

CS 331 DESIGN AND ANALYSIS OF ALGORITHMS DYNAMIC PROGRAMMING. Dr. Daisy Tang

A MODIFIED METHOD FOR SOLVING SYSTEM OF NONLINEAR EQUATIONS

Solution of Linear System of Equations and Matrix Inversion Gauss Seidel Iteration Method

On the Interval Zoro Symmetric Single-step Procedure for Simultaneous Finding of Polynomial Zeros

APPENDIX A Some Linear Algebra

ME 501A Seminar in Engineering Analysis Page 1

2. PROBLEM STATEMENT AND SOLUTION STRATEGIES. L q. Suppose that we have a structure with known geometry (b, h, and L) and material properties (EA).

CHAPTER 5 NUMERICAL EVALUATION OF DYNAMIC RESPONSE

Kernel Methods and SVMs Extension

Chapter Newton-Raphson Method of Solving a Nonlinear Equation

Mathematical Economics MEMF e ME. Filomena Garcia. Topic 2 Calculus

Chapter 14 Simple Linear Regression

EEE 241: Linear Systems

Anouncements. Multigrid Solvers. Multigrid Solvers. Multigrid Solvers. Multigrid Solvers. Multigrid Solvers

Topic 5: Non-Linear Regression

Polynomial Regression Models

A Hybrid Variational Iteration Method for Blasius Equation

Computational Biology Lecture 8: Substitution matrices Saad Mneimneh

Propagation of error for multivariable function

For now, let us focus on a specific model of neurons. These are simplified from reality but can achieve remarkable results.

PHYS 1441 Section 002 Lecture #15

Physics 2A Chapter 3 HW Solutions

A new Approach for Solving Linear Ordinary Differential Equations

NUMERICAL DIFFERENTIATION

Journal of Universal Computer Science, vol. 1, no. 7 (1995), submitted: 15/12/94, accepted: 26/6/95, appeared: 28/7/95 Springer Pub. Co.

A Simple Research of Divisor Graphs

Example: (13320, 22140) =? Solution #1: The divisors of are 1, 2, 3, 4, 5, 6, 9, 10, 12, 15, 18, 20, 27, 30, 36, 41,

( ) [ ( k) ( k) ( x) ( ) ( ) ( ) [ ] ξ [ ] [ ] [ ] ( )( ) i ( ) ( )( ) 2! ( ) = ( ) 3 Interpolation. Polynomial Approximation.

Lecture 26 Finite Differences and Boundary Value Problems

Module 3 LOSSY IMAGE COMPRESSION SYSTEMS. Version 2 ECE IIT, Kharagpur

Practical Newton s Method

= 1.23 m/s 2 [W] Required: t. Solution:!t = = 17 m/s [W]! m/s [W] (two extra digits carried) = 2.1 m/s [W]

Common loop optimizations. Example to improve locality. Why Dependence Analysis. Data Dependence in Loops. Goal is to find best schedule:

Limited Dependent Variables

Population element: 1 2 N. 1.1 Sampling with Replacement: Hansen-Hurwitz Estimator(HH)

The Multiple Classical Linear Regression Model (CLRM): Specification and Assumptions. 1. Introduction

ELE B7 Power Systems Engineering. Power Flow- Introduction

Parametric fractional imputation for missing data analysis. Jae Kwang Kim Survey Working Group Seminar March 29, 2010

Additional Codes using Finite Difference Method. 1 HJB Equation for Consumption-Saving Problem Without Uncertainty

MATH 829: Introduction to Data Mining and Analysis The EM algorithm (part 2)

Lecture 21: Numerical methods for pricing American type derivatives

Chapter 5. Solution of System of Linear Equations. Module No. 6. Solution of Inconsistent and Ill Conditioned Systems

University of Washington Department of Chemistry Chemistry 452/456 Summer Quarter 2014

Difference Equations

Spring Force and Power

ORDINARY DIFFERENTIAL EQUATIONS EULER S METHOD

STAT 309: MATHEMATICAL COMPUTATIONS I FALL 2018 LECTURE 16

The equation of motion of a dynamical system is given by a set of differential equations. That is (1)

Linear Approximation with Regularization and Moving Least Squares

Lecture 13 APPROXIMATION OF SECOMD ORDER DERIVATIVES

Least squares cubic splines without B-splines S.K. Lucas

Week3, Chapter 4. Position and Displacement. Motion in Two Dimensions. Instantaneous Velocity. Average Velocity

Lecture 2: Numerical Methods for Differentiations and Integrations

Curve Fitting with the Least Square Method

Chapter 4 The Wave Equation

Economics 130. Lecture 4 Simple Linear Regression Continued

Introduction to Vapor/Liquid Equilibrium, part 2. Raoult s Law:

Grid Generation around a Cylinder by Complex Potential Functions

Note 10. Modeling and Simulation of Dynamic Systems

PHYS 1443 Section 004 Lecture #12 Thursday, Oct. 2, 2014

Convexity preserving interpolation by splines of arbitrary degree

Lecture Notes on Linear Regression

Department of Quantitative Methods & Information Systems. Time Series and Their Components QMIS 320. Chapter 6

Local Approximation of Pareto Surface

COMPARISON OF SOME RELIABILITY CHARACTERISTICS BETWEEN REDUNDANT SYSTEMS REQUIRING SUPPORTING UNITS FOR THEIR OPERATIONS

Integrals and Invariants of Euler-Lagrange Equations

form, and they present results of tests comparng the new algorthms wth other methods. Recently, Olschowka & Neumaer [7] ntroduced another dea for choo

: 5: ) A

2.3 Nilpotent endomorphisms

Lecture 16 Statistical Analysis in Biomaterials Research (Part II)

Linear Correlation. Many research issues are pursued with nonexperimental studies that seek to establish relationships among 2 or more variables

Relaxation Methods for Iterative Solution to Linear Systems of Equations

CHAPTER 7 CONSTRAINED OPTIMIZATION 2: SQP AND GRG

x = , so that calculated

Digital Signal Processing

Absorbing Markov Chain Models to Determine Optimum Process Target Levels in Production Systems with Rework and Scrapping

Week 11: Chapter 11. The Vector Product. The Vector Product Defined. The Vector Product and Torque. More About the Vector Product

6.1 The function can be formulated as a fixed-point iteration as

Complex Variables. Chapter 18 Integration in the Complex Plane. March 12, 2013 Lecturer: Shih-Yuan Chen

Transcription:

CISE3: Numercal Methods Topc : Soluton o Nonlnear Equatons Dr. Amar Khoukh Term Read Chapters 5 and 6 o the tetbook CISE3_Topc c Khoukh_

Lecture 5 Soluton o Nonlnear Equatons Root ndng Problems Dentons Classcaton o methods Convergence Notatons CISE3_Topc c Khoukh_

Classcaton o methods CISE3_Topc c Khoukh_ 3

Root ndng Problems Many problems n Scence and Engneerng are epressed as Gven a contnuousuncton, nd thevalue r such that r These problems are called root ndng problems CISE3_Topc c Khoukh_ 4

Roots o Equatons A number r that satses an equaton s called a root o the equaton. Theequaton has our roots 4 3, 3, 3 7 3 and 5 8 So, one has 4 3 3 7 5 8 3 Theequaton has twosmpleroots and and a repeatedroot 3 wth multplcty CISE3_Topc c Khoukh_ 5

Zeros o a uncton Let be a real-valued uncton o a real varable. Any number r or whch r= s called a zero o the uncton. Eamples: and 3 are zeros o the uncton = --3 CISE3_Topc c Khoukh_ 6

Graphcal Interpretaton o zeros The real zeros o a uncton are the values o at whch the graph o the uncton crosses or touches the -as. Real zeros o CISE3_Topc c Khoukh_ 7

Smple Zeros has two smple zeros one at and one at CISE3_Topc c Khoukh_ 8

Multple Roots 3 has three zeros at - has zeros at two - s a zero o wth Multplcty = CISE3_Topc c Khoukh_ 9

Roots o Equatons & Zeros o uncton Gven theequaton 4 3 M oveall terms toone sde o theequaton 4 3 Dene as 4 3 3 3 3 7 7 7 5 8 5 5 8 8 The zeroso are thesame as the rootso theequaton Whch are, 3, 3 and zeros o the uncton are the roots o the equaton = CISE3_Topc c Khoukh_

Soluton Methods Several ways to solve nonlnear equatons are possble. Analytcal Solutons possble or specal equatons only Graphcal Solutons Useul or provdng ntal guesses or other methods Numercal Solutons Open methods Bracketng methods CISE3_Topc c Khoukh_

Soluton Methods: Analytcal Solutons Analytcal Solutons are avalable or specal equatons only. Analytcalsolutono a b c roots b b a 4ac Noanalytcalsoluton s avalable or e CISE3_Topc c Khoukh_

Graphcal Methods Graphcal methods are useul to provde an ntal guess to be used by other methods Solve e The root[,] e Root root.6 CISE3_Topc c Khoukh_ 3

Graphcal Interpretaton o zeros Plot =sn.+cos3. over [ 5] More detaled pcture over [, 5] Several roots wth a possble double root at 4. appearng as tangent to the -as. More narrowed scale over [4.3, 4.6] CISE3_Topc c Khoukh_ 4

Numercal Methods Many methods are avalable to solve nonlnear equatons Bsecton Method Newton s Method Secant Method False poston Method Muller s Method Barstow s Method Fed pont teratons. These wll be covered n SE3 CISE3_Topc c Khoukh_ 5

Bracketng Methods In bracketng methods, the method starts wth an nterval that contans the root and a procedure s used to obtan a smaller nterval contanng the root. Eamples o bracketng methods : Bsecton method False poston method CISE3_Topc c Khoukh_ 6

Open Methods In the open methods, the method starts wth one or more ntal guess ponts. In each teraton a new guess o the root s obtaned. Open methods are usually more ecent than bracketng methods They may not converge to the a root. CISE3_Topc c Khoukh_ 7

Convergence Notaton A sequence,,..., n,... s sad toconverge to to every there est N such that n n N CISE3_Topc c Khoukh_ 8

CISE3_Topc c Khoukh_ 9 Convergence Notaton C C C p n n n n n n order p Convergence o QuadratcConvergence Lnear Convergence to converges,...,, Let

Speed o convergence We can compare derent methods n terms o ther convergence rate. Quadratc convergence s aster than lnear convergence. A method wth convergence order q converges aster than a method wth convergence order p q>p. A Method o convergence order p> are sad to have super lnear convergence. CISE3_Topc c Khoukh_

Bsecton Method The Bsecton Algorthm Convergence Analyss o Bsecton Method Eamples Readng Assgnment: Sectons 5. and 5. CISE3_Topc c Khoukh_

Introducton: The Bsecton method s one o the smplest methods to nd a zero o a nonlnear uncton. It s also called nterval halvng method. Ths method needs an ntal nterval that s known to contan a zero o the uncton. Then ths nterval s systematcally reduced by dvdng t nto two equal parts. Based on a test on the product o the values o the uncton at nterval lmts, a hal o the nterval s thrown away. The procedure s repeated untl the desred nterval sze s obtaned. CISE3_Topc c Khoukh_

Intermedate Value Theorem Let be dened on the nterval [a,b], Intermedate value theorem: a uncton s contnuous and a and b have derent sgns then the uncton has at least one zero n the nterval [a,b] a a b b CISE3_Topc c Khoukh_ 3

Eamples I a and b have the same sgn, the uncton may have an even number o real zeros or no real zero n the nterval [a, b] Bsecton method can not be used n these cases a The uncton has our real zeros b a The uncton has no real zeros b CISE3_Topc c Khoukh_ 4

Two more Eamples I a and b have derent sgns, the uncton has at least one real zero Bsecton method can be used to nd one o the zeros. a The uncton has one real zero b a b The uncton has three real zeros CISE3_Topc c Khoukh_ 5

Bsecton Method Assumptons: Gven an nterval [a,b] s contnuous on [a,b] a and b have opposte sgns. These assumptons ensures the estence o at least one zero n the nterval [a,b] and the bsecton method can be used to obtan a smaller nterval that contans the zero. CISE3_Topc c Khoukh_ 6

Bsecton Algorthm Assumptons: s contnuous on [a,b] a b < a Algorthm: Loop. Compute the md pont c=a+b/. Evaluate c 3. I a c < then new nterval [a, c] I a c > then new nterval [c, b] End loop a c b b CISE3_Topc c Khoukh_ 7

Bsecton Method b a a a CISE3_Topc c Khoukh_ 8

Eample + + - + - - + + - CISE3_Topc c Khoukh_ 9

Flow chart o Bsecton Method Start: Gven a,b and ε u = a ; v = b c = a+b / ; w = c no yes s u w < no s b-a /<ε yes Stop b=c; v= w a=c; u= w CISE3_Topc c Khoukh_ 3

Eample Can youuse Bsectonmethod tonda zeroo 3 Answer: 3 n thenterval[,]? s * contnuouson [,] 3 Assumptons are not satsed Bsecton method can not be used 3 CISE3_Topc c Khoukh_ 3

Eample: Can youuse Bsectonmethod tonda zeroo 3 3 n thenterval[,]? Answer: s * contnuouson [,] Assumptons are - satsed Bsecton method can be used CISE3_Topc c Khoukh_ 3

Best Estmate and error level Bsecton method obtans an nterval that s guaranteed to contan a zero o the uncton Questons: What s the best estmate o the zero o? What s the error level n the obtaned estmate? CISE3_Topc c Khoukh_ 33

Best Estmate and error level The best estmate o the zero o the uncton s the md pont o the last nterval generated by the Bsecton method. Estmate o the zero r b a Error b a CISE3_Topc c Khoukh_ 34

Stoppng Crtera Two common stoppng crtera. Stop ater a ed number o teratons. Stop when the absolute error s less than a speced value How these crtera are related? CISE3_Topc c Khoukh_ 35

Stoppng Crtera c r n s themdpont o thentervalat then th teraton c n s usually used as the estmateo theroot. s thezeroo the uncton Ater n teratons error r -c n b a n CISE3_Topc c Khoukh_ 36

Convergence Analyss Gven, a, b and How many teratonsare needed such that where r s thezeroo and s the bsecton estmate.e. c k - r log b a log n log CISE3_Topc c Khoukh_ 37

Convergence Analyss Alternatve orm Gven How many where r, s a, b thezeroo bsecton estmate and teratonsare needed such that.e. and s c k the - r n wdth o ntal nterval log log wdth o desred nterval b a CISE3_Topc c Khoukh_ 38

Eample a 6, b 7,.5 How many teratons are needed such that - r CISE3_Topc c Khoukh_ 39

Eample a 6, b 7,.5 How many teratonsare needed such that - r n log b a log log log log. log 9.9658 n CISE3_Topc c Khoukh_ 4

Eample Use Bsecton method to nd a root o the equaton = cos wth absolute error <. assume the ntal nterval [.5,.9] Queston : What s? Queston : Are the assumptons satsed? Queston 3: How many teratons are needed? Queston 4: How to compute the new estmate? CISE3_Topc c Khoukh_ 4

CISE3_Topc c Khoukh_ 4

Bsecton Method Intal Interval a=-.3776 b =.784 a =.5 c=.7 b=.9 CISE3_Topc c Khoukh_ 43

Bsecton Method -.3776 -.648.784.5.7.9 Error <. -.648.33.784.7.8.9 Error <.5 CISE3_Topc c Khoukh_ 44

Bsecton Method -.648.83.33.7.75.8 Error <.5 -.648 -.35.83.7.75.75 Error <.5 CISE3_Topc c Khoukh_ 45

Summary Intal nterval contanng the root [.5,.9] Ater 4 teratons Interval contanng the root [.75,.75] Best estmate o the root s.7375 Error <.5 CISE3_Topc c Khoukh_ 46

Programmng Bsecton Method a=.5; b=.9; u=a-cosa; v= b-cosb; or =:5 c=a+b/ c=c-cosc u*c< b=c ; v=c; else a=c; u=c; end end c =.7 c = -.648 c =.8 c =.33 c =.75 c =.83 c =.75 c = -.35 CISE3_Topc c Khoukh_ 47

Eample Fnd the root o 3 3 n thenterval[,] * * * s contnuous, a b Bsecton method can be used to nd the root CISE3_Topc c Khoukh_ 48

Eample Iteraton a b c= a+b c b-a.5 -.375.5.5.5.66.5.5.5.375-7.3E-3.5 3.5.375.35 9.3E-.65 4.35.375.34375 9.37E-3.35 CISE3_Topc c Khoukh_ 49

Bsecton Method Advantages Smple and easy to mplement One uncton evaluaton per teraton The sze o the nterval contanng the zero s reduced by 5% ater each teraton The number o teratons can be determned a pror No knowledge o the dervatve s needed The uncton does not have to be derentable Dsadvantage Slow to converge Good ntermedate appromatons may be dscarded CISE3_Topc c Khoukh_ 5

Lecture 8-9 Newton-Raphson Method Assumptons Interpretaton Eamples Convergence Analyss CISE3_Topc c Khoukh_ 5

Newton-Raphson Method Also known as Newton s Method Gven an ntal guess o the root, Newton- Raphson method uses normaton about the uncton and ts dervatve at that pont to nd a better guess o the root. Assumptons: s contnuous and rst dervatve s known An ntal guess such that s gven CISE3_Topc c Khoukh_ 5

CISE3_Topc c Khoukh_ 53 Newton s Method end n or Assumputon Gven ' : ', ', END STOP CONTINUE X PRINT X FP X F X X I DO X X X X FP X X X F PROGRAM FORTRAN C *, /,5 4 6* ** 3* ** 3* **3

CISE3_Topc c Khoukh_ 54 Newton s Method end n or Assumputon Gven ' : ', ', end X FP X F X X or X MATLAB PROGRAM / :5 4 % X X FP X FP FP uncton X X F X F F uncton 6* ^ 3* ] [ ^ 3* ^3 ] [ F.m FP.m

Dervaton o Newton s Method Gven: Queston : Taylor Therorem: Fnd a h h new guess an ntal How do weobtan a better estmate? such that ' o guess theroot o h h theroot ' CISE3_Topc c Khoukh_ 55. o ' h

Eample 3 Fnd a zero o the uncton 3, 4 CISE3_Topc c Khoukh_ 56

CISE3_Topc c Khoukh_ 57 Eample.3 9.74.369.4375 ' 3: Iteraton.4375 6 9 3 ' : Iteraton 3 33 33 4 ' : Iteraton 4 3 ' 4, 3 theuncton zeroo Fnd a 3 3

Eample Iteraton k k k k+ k+ k 4 33 33 3 3 9 6.4375.565.4375.369 9.74.3.45 3.3.564 6.844.756.384 4.756.65 6.4969.746. CISE3_Topc c Khoukh_ 58

Convergence Analyss Theorem: Let where, such that C r ma -r mn ' and -r -r. I '' ' '' 'r k k -r be contnuous at -r then thereest C r CISE3_Topc c Khoukh_ 59

Convergence Analyss Remarks When the guess s close enough to a smple root o the uncton then Newton s method s guaranteed to converge quadratcally. Quadratc convergence means that the number o correct dgts s nearly doubled at each teraton. CISE3_Topc c Khoukh_ 6

Problems wth Newton s Method I the ntal guess o the root s ar rom the root the method may not converge. Newton s method converges lnearly near multple zeros { r = r = }. In such a case moded algorthms can be used to regan the quadratc convergence. CISE3_Topc c Khoukh_ 6

Problems wth Newton s Method Runaway The estmates o the root s gong away rom the root. CISE3_Topc c Khoukh_ 6

Problems wth Newton s Method Flat Spot The value o s zero, the algorthm als. I s very small then wll be very ar rom. CISE3_Topc c Khoukh_ 63

Problems wth Newton s Method Cycle = 3 = 5 = = 4 The algorthm cycles between two values and CISE3_Topc c Khoukh_ 64

CISE3_Topc c Khoukh_ 65 Newton s Method or Systems o Non Lnear Equatons ',,...,,..., ' ' o theroot o guess an ntal : X F X F X F X F X X Iteraton s Newton F X Gven k k k k

CISE3_Topc c Khoukh_ 66 Eample Solve the ollowng system o equatons, guess Intal 5 5 y y y. y, 5 5 ', 5 5 X y F y y. y F

CISE3_Topc c Khoukh_ 67 Soluton Usng Newton s Method.6.33 -.5.65 7.5.5.5.5.5 7.5.5.5 ', -.5.65 Iteraton :.5.5 5 6 6 5 5 ', 5 5 5 : Iteraton X F F. X y F. y y. y F

CISE3_Topc c Khoukh_ 68 Eample Try ths Solve the ollowng system o equatons, guess Intal y y y y, 4 ', X y F y y y F

CISE3_Topc c Khoukh_ 69 Eample Soluton.98.557.98.557.969.587..6 5 4 3 X k Iteraton

Lectures Secant Method Secant Method Eamples Convergence Analyss CISE3_Topc c Khoukh_ 7

Newton s Method Revew Assumptons :, ', Newton' s Method newestmate Problem: ' ' s not avalable ' or dcult toobtan analytcally CISE3_Topc c Khoukh_ 7 are avalable,

CISE3_Topc c Khoukh_ 7 Secant Method ' ponts are twontal ' and h h

CISE3_Topc c Khoukh_ 73 Secant Method NewestmateSecant M ethod: ponts Two ntal s : Assumpton that such and

CISE3_Topc c Khoukh_ 74 Secant Method.5

CISE3_Topc c Khoukh_ 75 Secant Method ;,, Stop NO Yes

CISE3_Topc c Khoukh_ 76 Moded Secant Method dverge themethod may selected properly, not I? Problem: How toselect ' needed s guess onental ths moded Secant methodonly In

Eample 5 nd therootso ntal ponts 5 and 3 3. 4 3 - wth error. - -3-4 - -.5 - -.5.5.5 CISE3_Topc c Khoukh_ 77

Eample + +- -.. -..585 -.6. 6 -.6. -.5.9 -.5. -.5. CISE3_Topc c Khoukh_ 78

Convergence Analyss The rate o convergence o the Secant method s super lnear r r r : root C,.6 : estmateo theroot at the teraton It s better than Bsecton method but not as good as Newton s method th CISE3_Topc c Khoukh_ 79

Lectures Comparson o Root ndng methods Advantages/dsadvantages Eamples CISE3_Topc c Khoukh_ 8

Summary Bsecton Newton Secant Relable, Slow One uncton evaluaton per teraton Needs an nterval [a,b] contanng the root, a b< No knowledge o dervatve s needed Fast near the root but may dverge Two uncton evaluaton per teraton Needs dervatve and an ntal guess, s nonzero Fast slower than Newton but may dverge one uncton evaluaton per teraton Needs two ntal ponts guess, such that - s nonzero. No knowledge o dervatve s needed CISE3_Topc c Khoukh_ 8

CISE3_Topc c Khoukh_ 8 Eample.5 ponts Two ntal theroot o UseSecant method to nd 6 and

Soluton k k k. -..5 8.896.56 -.76 3.836 -.4645 4.47.3 5.33 -.65 6.347 -.5 CISE3_Topc c Khoukh_ 83

Eample Use Newton' s M ethodto nd a root o 3 Use the Stop ater ntal ponts threeteratons or k k. or k. CISE3_Topc c Khoukh_ 84

Fve teratons o the soluton k k k k ERROR. -...5.875 5.75.5.3478.7 4.4499.6 3.35. 4.685.5 4.347. 4.646. 5.347. 4.646. CISE3_Topc c Khoukh_ 85

Eample Use Newton' s M ethodto nd a root o e Use the Stop ater ntal ponts threeteratons or k k. or k. CISE3_Topc c Khoukh_ 86

Eample Use Newton' s e, M ethodto ' nd e a root o k. k -.63 ' k -.3679 ' k k.46.5379.46 -.584 -.9.567. -.567 -..567. -.567 -. CISE3_Topc c Khoukh_ 87

Eample In estmatng the root o -cos= To get more than 3 correct dgts 4 teratons o Newton =.6 43 teratons o Bsecton method ntal nterval [.6,.8] 5 teratons o Secant method =.6, =.8 CISE3_Topc c Khoukh_ 88

Homework Assgnment Check the webct or the HW and due date CISE3_Topc c Khoukh_ 89