Docsity
Docsity

Prepare for your exams
Prepare for your exams

Study with the several resources on Docsity


Earn points to download
Earn points to download

Earn points by helping other students or get them with a premium plan


Guidelines and tips
Guidelines and tips

Secant Method - Numerical Analysis - Solved Exam, Exams of Mathematical Methods for Numerical Analysis and Optimization

Main Points are:Secant Method, Solving Nonlinear Equations, Newton-Raphson Method, Symbolic Manipulators, Geometrical Representation, Finding Roots of Equations, End of Iteration, Function of Iterations, Significant Digits

Typology: Exams

2012/2013

Uploaded on 04/16/2013

maalolan
maalolan 🇮🇳

4.5

(8)

123 documents

1 / 4

Toggle sidebar

This page cannot be seen from the preview

Don't miss anything!

bg1
03.05.1
Chapter 03.05
Secant Method of Solving Nonlinear Equations
After reading this chapter, you should be able to:
1. derive the secant method to solve for the roots of a nonlinear equation,
2. use the secant method to numerically solve a nonlinear equation.
What is the secant method and why would I want to use it instead of the Newton-
Raphson method?
The Newton-Raphson method of solving a nonlinear equation 0)( xf is given by the
iterative formula
)(
)(
1
i
i
ii xf
xf
= xx
(1)
One of the drawbacks of the Newton-Raphson method is that you have to evaluate the
derivative of the function. With availability of symbolic manipulators such as Maple,
MathCAD, MATHEMATICA and MATLAB, this process has become more convenient.
However, it still can be a laborious process, and even intractable if the function is derived as
part of a numerical scheme. To overcome these drawbacks, the derivative of the function,
)(xf is approximated as
1
1)()(
)(
ii
ii
ixx
xfxf
xf (2)
Substituting Equation (2) in Equation (1) gives
)()(
))((
1
1
1
ii
iii
ii xfxf
xxxf
xx (3)
The above equation is called the secant method. This method now requires two initial
guesses, but unlike the bisection method, the two initial guesses do not need to bracket the
root of the equation. The secant method is an open method and may or may not converge.
However, when secant method converges, it will typically converge faster than the bisection
method. However, since the derivative is approximated as given by Equation (2), it typically
converges slower than the Newton-Raphson method.
Docsity.com
pf3
pf4

Partial preview of the text

Download Secant Method - Numerical Analysis - Solved Exam and more Exams Mathematical Methods for Numerical Analysis and Optimization in PDF only on Docsity!

Chapter 03.

Secant Method of Solving Nonlinear Equations

After reading this chapter, you should be able to:

  1. derive the secant method to solve for the roots of a nonlinear equation,
  2. use the secant method to numerically solve a nonlinear equation.

What is the secant method and why would I want to use it instead of the Newton-

Raphson method?

The Newton-Raphson method of solving a nonlinear equation f ( x ) 0 is given by the

iterative formula

1 i

i i i f x

f x x = x

One of the drawbacks of the Newton-Raphson method is that you have to evaluate the

derivative of the function. With availability of symbolic manipulators such as Maple,

MathCAD, MATHEMATICA and MATLAB, this process has become more convenient.

However, it still can be a laborious process, and even intractable if the function is derived as

part of a numerical scheme. To overcome these drawbacks, the derivative of the function,

f ( x )is approximated as

1

i i

i i i x x

f x f x f x (2)

Substituting Equation (2) in Equation (1) gives

1

1 1 

  

i i

i i i i i f x f x

f x x x x x (3)

The above equation is called the secant method. This method now requires two initial

guesses, but unlike the bisection method, the two initial guesses do not need to bracket the

root of the equation. The secant method is an open method and may or may not converge.

However, when secant method converges, it will typically converge faster than the bisection

method. However, since the derivative is approximated as given by Equation (2), it typically

converges slower than the Newton-Raphson method.

03.05.2 Chapter 03.

The secant method can also be derived from geometry, as shown in Figure 1. Taking two

initial guesses, xi (^)  1 and xi , one draws a straight line between f ( xi ) and f ( xi  1 ) passing

through the x -axis at xi (^)  1. ABE and DCE are similar triangles.

Hence

DE

DC

AE

AB

1 1

1

1

 

 (^) i i

i

i i

i

x x

f x

x x

f x

On rearranging, the secant method is given as

1

1 1 

  

i i

i i i i i f x f x

f x x x x x

Figure 1 Geometrical representation of the secant method.

Example 1

You are working for ‘DOWN THE TOILET COMPANY’ that makes floats (Figure 2) for

ABC commodes. The floating ball has a specific gravity of 0.6 and a radius of 5.5 cm. You

are asked to find the depth to which the ball is submerged when floating in water.

The equation that gives the depth x to which the ball is submerged under water is given by

  1. 165 3. 993 10 0

3 2 4    

x x

Use the secant method of finding roots of equations to find the depth x to which the ball is

submerged under water. Conduct three iterations to estimate the root of the above equation.

Find the absolute relative approximate error and the number of significant digits at least

correct at the end of each iteration.

f ( x )

f ( xi )

f ( xi– 1 )

xi+ 1 xi– 1 xi

x

B

C

E D A

03.05.4 Chapter 03.

3 2 4 3 2 4

3 2 4

 

The absolute relative approximate error  a at the end of Iteration 2 is

2

2 1 

x

x x a

The number of significant digits at least correct is 1, as you need an absolute relative

approximate error of 5% or less.

Iteration 3

2 2 1 3 2 f x f x

f x x x x x

2 4 1

3 1

2 4 2

3 2

2 1

2 4 2

3 2 2

  1. 165 3. 993 10 0. 165 3. 993 10

 

x x x x

x x x x x

3 2 4 3 2 4

3 2 4

 

The absolute relative approximate error  a at the end of Iteration 3 is

3

3 2 

x

x x a

The number of significant digits at least correct is 2, as you need an absolute relative

approximate error of 0.5% or less. Table 1 shows the secant method calculations for the

results from the above problem.

Table 1 Secant method results as a function of iterations.

Iteration

Number, i

x i  1 xi xi  1  a % f  xi  1 

4

  1. 64 10

  

5

  1. 9812 10

   7

  1. 2852 10

   9

  1. 0252 10

  13

  1. 8576 10

  