Does this method have a name? Function Approximation by Polynomial Sum

In summary, the conversation discusses a method for approximating a function and extending its domain from Natural numbers to Real numbers. The method involves adding polynomials of increasing degree to make the approximation function equal to the function at specific points. However, it may not work well for certain functions and may require additional work to be useful. The conversation also mentions the use of similar ideas in digital signal processing and numerical methods in various fields. The participants also mention Taylor series and its potential application to the method.
  • #1
Swimmingly!
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I created a method for both approximating a function and extending a it's domain from a Natural to a Real Domain. Does this have a name already or any interesting application?
Basically. Add polynomial of degree 0, 1, 2, 3, etc. Making at the same time the approximation function equal to f(0), f(1), f(2), f(3), etc.

The approximation of function f is:
App. of f http://latex.codecogs.com/examples/a0d1659d13fd1904ffe767edc6cab6e4.gif
n is level of the approximation, the bigger the n the bigger the approximation and the more the polynomia.
http://latex.codecogs.com/examples/10d3e8addce0f1cea366f3eafcae03df.gif =f(n)-App. of f at n of level (n-1)
http://latex.codecogs.com/examples/00d8763b00aac3dd87168ec5039ec758.gif
http://latex.codecogs.com/examples/92cf5169e1dbb1a99d49de59187bc652.gif
etc.

The idea is actually very simple! Just add a constant and then a line and then a parabola, etc to make it similar to the function.
Also can anyone find a simpler way to find the coefficients. E? Maybe for f(x)=x! ?
 
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  • #3
The general idea behind this is a good one (and kudos if you thought it out for yourself) but it needs some more work to make it "useful".

For example suppose you approximate the function ##f(x) = \sin \pi x##. That is 0 at every integer point x = 1, 2, 3 ... so your approximation will always to 0.

If you plot out the successive approximations to functions like ##f(x) = 2^x## or ##f(x) = 2^{-x}## you will probably see something bad happening, as well.

But a slightly different version of this idea IS used in digital signal processing, where you are only interested in a restricted set of functions that excludes the examples I just gave. This is much too big a topic to write a summary here, but you might like to explore it on the web.

Similar ideas are also used for fitting curves through an arbitrary set of points, and in the numerical methods used in Finite Element structural mechanics, computational fluid dynamics, etc.
 
  • #4
Vorde said:
Do you know about Taylor Series?: http://en.wikipedia.org/wiki/Taylor_series

It seems like you are edging towards this.

I knew about it thanks. I think I thought of this when I heard about Taylor series and I was guessing what it was.


AlephZero:

It looks bad with functions like sin(πx) and x^n; it looks too symmetric; it's limit is almost always + or - infinity; it completely ignores the negative of the function.
But some problems would maybe be partially solved if I could find a way to take the limit as n goes to infinity. Help would be appreciated if possible. This math is messy unfortunately.

I'll have a look at those other methods. Maybe they'll be helpful, thank you.
 

1. What is function approximation?

Function approximation is a mathematical technique used to find a simplified representation of a complex function. It involves finding a simpler function, such as a polynomial, that closely resembles the original function.

2. Why is function approximation important?

Function approximation is important because it allows us to approximate complex functions with simpler ones, making it easier to analyze and manipulate them. It also allows us to make predictions and solve problems that would otherwise be too complicated to solve.

3. What is polynomial sum?

Polynomial sum is a method used in function approximation where a polynomial function is used to approximate a more complex function. It involves adding together multiple polynomial functions with different coefficients to closely match the original function.

4. How does the method of polynomial sum work?

The method of polynomial sum works by finding the coefficients of multiple polynomial functions and adding them together to create a final approximation of the original function. This process involves minimizing the error between the original function and the polynomial sum.

5. Are there any limitations to function approximation by polynomial sum?

Yes, there are limitations to function approximation by polynomial sum. This method may not be suitable for highly non-linear functions, and the accuracy of the approximation depends on the number of polynomial functions used and their chosen coefficients. Additionally, it may not work well for functions with discontinuities or sharp changes in behavior.

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