Rational function that approximates e^x

In summary, Woolfram gives a couple of continued fraction expressions for e^x; truncating these will give you a rational function approximation. But it is better to use a library function for exp if at all possible.
  • #1
Ledsnyder
26
0
Is there a rational function,not series, that approximates e^x
?
for example (x+1)/(x+3)
 
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  • #2
What do you mean by "approximates"? A given function, rational or not, has a specific difference from [itex]e^x[/itex]. We can always find a function, for example by truncating the Taylor's series to a polynomial, that "approximates" [itex]e^x[/itex] to a desired degree of accuracy. The difference is that the series, [itex]\sum_{n=0}^\infty[/itex] does NOT 'approximate' [itex]e^x[/itex], it is exactly equal to it.
 
  • #4
That is not at all the question you asked before. However, the standard Taylor's series for the exponential, [tex]\sum_{n=0}^\infty \frac{x^n}{n!}[/tex]
is a very "rapid" approximation to the exponential.
 
  • #5
HallsofIvy said:
That is not at all the question you asked before. However, the standard Taylor's series for the exponential, [tex]\sum_{n=0}^\infty \frac{x^n}{n!}[/tex]
is a very "rapid" approximation to the exponential.

Truncating the series after a fixed number of terms is not a good method of evaluating [itex]e^x[/itex] numerically for large [itex]|x|[/itex], since one loses precision from calculating the large values of [itex]x^n[/itex] and [itex]n![/itex] and the remainder may be large.

To the OP: Woolfram gives a couple of continued fraction expressions for [itex]e^x[/itex]; truncating these will give you a rational function approximation. But it is better to use a library function for exp if at all possible.
 
  • #6
1+x.
 
  • #7
It depends what type of approximation you want. One common one is an approximation such that the function and its derivatives match the approximation up to some degree

$$
e^{-x}\sim P(x)/Q(x)\\
\text{where}\\
P(x)=\sum_{k=0}^m \frac{(m+n-k)!m!}{(m+n)!k!(m-k)!}x^k
\\
Q(x)=\sum_{k=0}^n \frac{(m+n-k)!n!}{(m+n)!k!(n-k)!}x^k
$$

matches up to the n+m+1 derivative

see
http://mathworld.wolfram.com/PadeApproximant.html
http://en.wikipedia.org/wiki/Padé_table#An_example_.E2.80.93_the_exponential_function
http://wwwhome.math.utwente.nl/~vajtam/publications/temp00-pade.pdf
 

FAQ: Rational function that approximates e^x

What is a rational function that approximates e^x?

A rational function that approximates e^x is a mathematical expression in the form of a ratio of two polynomials, which can closely mimic the behavior of the natural exponential function e^x for a given range of values.

How is a rational function used to approximate e^x?

A rational function is used to approximate e^x by finding the coefficients of the numerator and denominator polynomials that best fit the values of e^x for a given range of inputs. This can be done using various mathematical techniques such as Taylor series or Padé approximation.

Why is it important to have a rational function that approximates e^x?

Having a rational function that approximates e^x is important because it allows us to calculate values of the natural exponential function for a wider range of inputs, without having to resort to complex and time-consuming calculations of the actual function. This can be especially useful in practical applications where quick and accurate approximations are needed.

What are the limitations of using a rational function to approximate e^x?

While a rational function can closely approximate e^x for a given range of inputs, it is not an exact representation of the natural exponential function. As the input values increase or decrease beyond the chosen range, the accuracy of the approximation decreases. Additionally, the choice of the range and the method used for approximation can also affect the accuracy of the results.

How can we improve the accuracy of a rational function that approximates e^x?

The accuracy of a rational function that approximates e^x can be improved by choosing a larger range of input values, using higher-order polynomials, or using more advanced approximation techniques such as Chebyshev approximation. It is also important to carefully select the range and method of approximation based on the specific needs of the application.

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