Newton's method for approximating solutions of functions

In summary, the formula for approximating a function's solution using an approximated tangent function is derived from Taylor's formula when only the first term is used. This method is known as Newton's method and can provide a good approximation for the root value of a function under certain conditions.
  • #1
stratz
23
0
In my calculus textbook, it shows that a function's solution can be approximated using an approximated function tangent to the original function based on an approximated solution, where the equation to find the approximated is L(x) = f(X0) + f'(X0)*(X-X0), where when rearranged, gives x = Xo - (f(X0)/f'(X0)) it doesn't give any reasoning as to why this is the equation. I do understand that the f(X0)/f'(X0) does in some way represent the margin of error of X0, and would (asymptotically) approach this margin of error, but never fully reach it (at least in the cases of the example equations given by the textbook). However, I would like to know how it works and how this equation was derived.

Any help would be appreciated, thanks.
 
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  • #2
The formula works if you have got a starting value close to the solution. L(x) is Taylor's formula when only the first term is used.
 
  • #3
stratz said:
In my calculus textbook, it shows that a function's solution can be approximated using an approximated function tangent to the original function based on an approximated solution, where the equation to find the approximated is L(x) = f(X0) + f'(X0)*(X-X0), where when rearranged, gives x = Xo - (f(X0)/f'(X0)) it doesn't give any reasoning as to why this is the equation. I do understand that the f(X0)/f'(X0) does in some way represent the margin of error of X0, and would (asymptotically) approach this margin of error, but never fully reach it (at least in the cases of the example equations given by the textbook). However, I would like to know how it works and how this equation was derived.
It's really not very complicated.

You have a curve y = f(x), with a known point ##(x_0, f(x_0))## on the curve, and you know the slope of the tangent, ##f'(x_0)## at that point. Run a line segment from ##(x_0, f(x_0))## down the tangent line to where it intersects the x-axis. That x value, ##x_1## is your first approximation to the root, the value of x for which f(x) = 0. You should be able to find the equation of this tangent line and work out what ##x_1## would be.

Newton's method continues the process using a new point, ##(x_1, f(x_1))## and known derivative value, ##f'(x_1)## to get another approximation for the root, ##x_2##. Under certain conditions, the method converges pretty rapidly, but in other conditions, it doesn't.

Most calculus books show how this formula is derived.
 

Related to Newton's method for approximating solutions of functions

1. What is Newton's method for approximating solutions of functions?

Newton's method is an iterative algorithm used to find the roots of a differentiable function. It starts with an initial guess and uses the tangent line at that point to find a better approximation of the root. This process is repeated until a desired level of accuracy is achieved.

2. How does Newton's method work?

Newton's method works by using the slope of the tangent line at a given point to find a better approximation of the root. It then repeats this process with the new approximation until the desired level of accuracy is reached. The formula for Newton's method is:
xn+1 = xn - f(xn) / f'(xn)

3. What are the advantages of using Newton's method?

One of the main advantages of Newton's method is that it can quickly converge to the root of a function. It also has a quadratic convergence rate, meaning that the number of accurate digits roughly doubles with each iteration. Additionally, it can handle complex functions and multiple roots.

4. What are the limitations of Newton's method?

One limitation of Newton's method is that it requires knowledge of the derivative of the function, which may not always be readily available. It can also fail to converge if the initial guess is too far from the root or if the function has multiple roots close together. Additionally, it may get stuck in a local minimum or maximum instead of finding the global minimum or maximum.

5. How is Newton's method used in real-life applications?

Newton's method is commonly used in various fields of science and engineering to solve complex problems. It is particularly useful in optimization and root-finding problems, such as finding the roots of a polynomial or determining the maximum or minimum of a function. It is also used in financial modeling, computer graphics, and machine learning.

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