Functional differentiation: Difference between revisions
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There are several ways to do this: | There are several ways to do this: | ||
* Approximate the derivative <math>f'(x)</math> by <math>\frac{f(x+h)-f(x)}{h}</math> where <math>h</math> is close to zero. (or at best the square root of the machine precision <math>\varepsilon</math>. | * Approximate the derivative <math>f'(x)</math> by <math>\frac{f(x+h)-f(x)}{h}</math> where <math>h</math> is close to zero. (or at best the square root of the machine precision <math>\varepsilon</math>. | ||
* Compute the derivative of <math>f</math> symbolically. This approach is particularly interesting for Haskell. | * Compute the derivative of <math>f</math> [[Typeful_symbolic_differentiation|symbolically]]. This approach is particularly interesting for Haskell. | ||
== Blog Posts == | == Blog Posts == | ||
Revision as of 15:54, 20 June 2007
Introduction
Functional differentiation means computing or approximating the deriviative of a function. There are several ways to do this:
- Approximate the derivative by where is close to zero. (or at best the square root of the machine precision .
- Compute the derivative of symbolically. This approach is particularly interesting for Haskell.
Blog Posts
There have been several blog posts on this recently. I think we should gather the information together and make a nice wiki article on it here. For now, here are links to articles on the topic.