<< Chapter < Page Chapter >> Page >
  • Describe the steps of Newton’s method.
  • Explain what an iterative process means.
  • Recognize when Newton’s method does not work.
  • Apply iterative processes to various situations.

In many areas of pure and applied mathematics, we are interested in finding solutions to an equation of the form f ( x ) = 0 . For most functions, however, it is difficult—if not impossible—to calculate their zeroes explicitly. In this section, we take a look at a technique that provides a very efficient way of approximating the zeroes of functions . This technique makes use of tangent line approximations and is behind the method used often by calculators and computers to find zeroes.

Describing newton’s method

Consider the task of finding the solutions of f ( x ) = 0 . If f is the first-degree polynomial f ( x ) = a x + b , then the solution of f ( x ) = 0 is given by the formula x = b a . If f is the second-degree polynomial f ( x ) = a x 2 + b x + c , the solutions of f ( x ) = 0 can be found by using the quadratic formula. However, for polynomials of degree 3 or more, finding roots of f becomes more complicated. Although formulas exist for third- and fourth-degree polynomials, they are quite complicated. Also, if f is a polynomial of degree 5 or greater, it is known that no such formulas exist. For example, consider the function

f ( x ) = x 5 + 8 x 4 + 4 x 3 2 x 7 .

No formula exists that allows us to find the solutions of f ( x ) = 0 . Similar difficulties exist for nonpolynomial functions. For example, consider the task of finding solutions of tan ( x ) x = 0 . No simple formula exists for the solutions of this equation. In cases such as these, we can use Newton’s method to approximate the roots.

Newton’s method    makes use of the following idea to approximate the solutions of f ( x ) = 0 . By sketching a graph of f , we can estimate a root of f ( x ) = 0 . Let’s call this estimate x 0 . We then draw the tangent line to f at x 0 . If f ( x 0 ) 0 , this tangent line intersects the x -axis at some point ( x 1 , 0 ) . Now let x 1 be the next approximation to the actual root. Typically, x 1 is closer than x 0 to an actual root. Next we draw the tangent line to f at x 1 . If f ( x 1 ) 0 , this tangent line also intersects the x -axis, producing another approximation, x 2 . We continue in this way, deriving a list of approximations: x 0 , x 1 , x 2 ,… . Typically, the numbers x 0 , x 1 , x 2 ,… quickly approach an actual root x * , as shown in the following figure.

This function f(x) is drawn with points (x0, f(x0)), (x1, f(x1)), and (x2, f(x2)) marked on the function. From (x0, f(x0)), a tangent line is drawn, and it strikes the x axis at x1. From (x0, f(x0)), a tangent line is drawn, and it strikes the x axis at x2. If a tangent line were drawn from (x2, f(x2)), it appears that it would come very close to x*, which is the actual root. Each tangent line drawn in this order appears to get closer and closer to x*.
The approximations x 0 , x 1 , x 2 ,… approach the actual root x * . The approximations are derived by looking at tangent lines to the graph of f .

Now let’s look at how to calculate the approximations x 0 , x 1 , x 2 ,… . If x 0 is our first approximation, the approximation x 1 is defined by letting ( x 1 , 0 ) be the x -intercept of the tangent line to f at x 0 . The equation of this tangent line is given by

y = f ( x 0 ) + f ( x 0 ) ( x x 0 ) .

Therefore, x 1 must satisfy

f ( x 0 ) + f ( x 0 ) ( x 1 x 0 ) = 0 .

Solving this equation for x 1 , we conclude that

x 1 = x 0 f ( x 0 ) f ( x 0 ) .

Similarly, the point ( x 2 , 0 ) is the x -intercept of the tangent line to f at x 1 . Therefore, x 2 satisfies the equation

x 2 = x 1 f ( x 1 ) f ( x 1 ) .

In general, for n > 0 , x n satisfies

x n = x n 1 f ( x n 1 ) f ( x n 1 ) .

Next we see how to make use of this technique to approximate the root of the polynomial f ( x ) = x 3 3 x + 1 .

Questions & Answers

how do you get the 2/50
Abba Reply
number of sport play by 50 student construct discrete data
Aminu Reply
width of the frangebany leaves on how to write a introduction
Theresa Reply
Solve the mean of variance
Veronica Reply
Step 1: Find the mean. To find the mean, add up all the scores, then divide them by the number of scores. ... Step 2: Find each score's deviation from the mean. ... Step 3: Square each deviation from the mean. ... Step 4: Find the sum of squares. ... Step 5: Divide the sum of squares by n – 1 or N.
kenneth
what is error
Yakuba Reply
Is mistake done to something
Vutshila
Hy
anas
hy
What is the life teble
anas
hy
Jibrin
statistics is the analyzing of data
Tajudeen Reply
what is statics?
Zelalem Reply
how do you calculate mean
Gloria Reply
diveving the sum if all values
Shaynaynay
let A1,A2 and A3 events be independent,show that (A1)^c, (A2)^c and (A3)^c are independent?
Fisaye Reply
what is statistics
Akhisani Reply
data collected all over the world
Shaynaynay
construct a less than and more than table
Imad Reply
The sample of 16 students is taken. The average age in the sample was 22 years with astandard deviation of 6 years. Construct a 95% confidence interval for the age of the population.
Aschalew Reply
Bhartdarshan' is an internet-based travel agency wherein customer can see videos of the cities they plant to visit. The number of hits daily is a normally distributed random variable with a mean of 10,000 and a standard deviation of 2,400 a. what is the probability of getting more than 12,000 hits? b. what is the probability of getting fewer than 9,000 hits?
Akshay Reply
Bhartdarshan'is an internet-based travel agency wherein customer can see videos of the cities they plan to visit. The number of hits daily is a normally distributed random variable with a mean of 10,000 and a standard deviation of 2,400. a. What is the probability of getting more than 12,000 hits
Akshay
1
Bright
Sorry i want to learn more about this question
Bright
Someone help
Bright
a= 0.20233 b=0.3384
Sufiyan
a
Shaynaynay
How do I interpret level of significance?
Mohd Reply
It depends on your business problem or in Machine Learning you could use ROC- AUC cruve to decide the threshold value
Shivam
how skewness and kurtosis are used in statistics
Owen Reply
yes what is it
Taneeya
Got questions? Join the online conversation and get instant answers!
Jobilize.com Reply
Practice Key Terms 2

Get Jobilize Job Search Mobile App in your pocket Now!

Get it on Google Play Download on the App Store Now




Source:  OpenStax, Calculus volume 1. OpenStax CNX. Feb 05, 2016 Download for free at http://cnx.org/content/col11964/1.2
Google Play and the Google Play logo are trademarks of Google Inc.

Notification Switch

Would you like to follow the 'Calculus volume 1' conversation and receive update notifications?

Ask