Taylor Series for Any (x) = Function (x) for Any (x) ?

In summary, the Taylor series is a way to approximate a function using a polynomial expansion. For polynomials, the Taylor expansion will equal the function if enough terms are taken. However, for more complex functions, the Taylor series may not be equal to the function but rather converge to it. Analytic functions are the specific class of functions for which the Taylor series will always be equal to the function in some neighborhood.
  • #1
morrobay
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When a Taylor Series is generated from a functions n derivatives at a single point,
then is that series for any value of x equal to the original function for any value x ?
For example graph the original function (x) from x= 0 to x = 10.
Now plug into the Taylor Expansion for x , values from 0 to 10 and graph.
Are the two plots approximate or equal ?
Numerical example not to be worked but just for question :
Suppose f(x) = 4x^3 + 8x^2 - 3x +2
 
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  • #2
Hi morrobay! :smile:

In your example, you just have a polynomial, which means that the Taylor expansion will equal the function if the expansion is taken far enough (i.e. if you take 4 terms in the expansion).

In general, a polynomial will always equal the Taylor expansion if you take the expansion far enough.

A more interesting case are things like sin(x). The Taylor expansion of sine will never really equal the sine but it will converge to it. That is, the more terms in the expansion you take, the better the expansion will approximate the sine.
For example, if you take 6 terms, then you get quite a good approximation:

[tex]sin(x)\sim x-\frac{x^3}{3!}+\frac{x^6}{6!}[/tex]

When you take the entire Taylor series (that is: when you take all the terms), then you get equality:

[tex]\sin(x)=\sum_{k=0}^{+\infty}{\frac{(-1)^nx^{2n+1}}{(2n+1)!}}[/tex]

However, there are certain functions in which the Taylor expansions do not approximate the function well. Take the Taylor expansion of log(x) at 1. For points larger than 2, the Taylor expansions form very, very bad approximations of the function.
 
  • #3
Even more interesting is the Taylor series for [itex]f(x)= e^{-1/x}[/itex] if x is not 0, 0 if x= 0. That is infinitely differentiableat x= 0 and repeated derivatives are rational functions time [itex]e^{-1/x}[/itex] if x is not 0, 0 if x is 0. That is, the Taylor series for this function exists and is identically 0 for all 0. Clearly, f(x) is not 0 except at x= 0 so this is a function whose Taylor series exist for all x but is not equal to the function value except at x= 0.

So, no, for general functions, the Taylor's series is not necessarily equal to the function value. The "analytic functions" are specifically defined to be those for which it is true: a function is analytic, at x= a, if and only if its Taylor's series at x= a is equal to the function value for all x in some neighborhood of a.
 

FAQ: Taylor Series for Any (x) = Function (x) for Any (x) ?

What is a Taylor Series?

A Taylor Series is a mathematical representation of a function using an infinite sum of terms. It is used to approximate a function by breaking it down into smaller, more manageable pieces.

How is a Taylor Series calculated?

A Taylor Series is calculated by taking the derivatives of a function at a specific point and plugging them into a formula. The formula is: f(x) = f(a) + f'(a)(x-a) + f''(a)(x-a)^2/2! + ... + fn(a)(x-a)^n/n!, where a is the point at which the derivatives are taken.

What is the purpose of a Taylor Series?

The purpose of a Taylor Series is to approximate a function at a specific point. It can also be used to find the behavior of a function near a certain point, such as determining if a function is increasing or decreasing.

Can a Taylor Series be used for any function?

Yes, a Taylor Series can be used for any function as long as it is infinitely differentiable at the point at which the series is being calculated. This means that the function must have derivatives of all orders at that point.

How accurate is a Taylor Series approximation?

The accuracy of a Taylor Series approximation depends on the number of terms used in the series. The more terms that are included, the more accurate the approximation will be. However, using too many terms can result in computational errors. It is important to determine the appropriate number of terms to use for the desired level of accuracy.

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