Difference between revisions of "Functional differentiation"

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* [http://sigfpe.blogspot.com/2005/07/automatic-differentiation.html Automatic Differentiation]
 
* [http://sigfpe.blogspot.com/2005/07/automatic-differentiation.html Automatic Differentiation]
 
* [http://cdsmith.wordpress.com/2007/11/29/some-playing-with-derivatives/ Some Playing with Derivatives]
 
* [http://cdsmith.wordpress.com/2007/11/29/some-playing-with-derivatives/ Some Playing with Derivatives]
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== Code ==
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* [http://hackage.haskell.org/package/fad Forward accumulation mode Automatic Differentiation] Hackage package
  
 
[[Category:Mathematics]]
 
[[Category:Mathematics]]

Revision as of 12:16, 27 April 2010

Introduction

Functional differentiation means computing or approximating the derivative of a function. There are several ways to do this:

  • Approximate the derivative f'(x) by \frac{f(x+h)-f(x)}{h} where h is close to zero. (or at best the square root of the machine precision \varepsilon.
  • Compute the derivative of f symbolically. This approach is particularly interesting for Haskell.

Functional analysis

If you want to explain the terms Higher order function and Currying to mathematicians, this is certainly a good example. The mathematician writes

 D f (x) = \lim_{h\to 0} \frac{f(x+h)-f(x)}{h}

and the Haskell programmer writes

derive :: a -> (a -> a) -> (a -> a)
derive h f x = (f (x+h) - f x) / h    .

Haskell's derive h approximates the mathematician's  D . In functional analysis  D is called a (linear) function operator, because it maps functions to functions. In Haskell derive h is called a higher order function for the same reason.  D is in curried form. If it would be uncurried, you would write  D(f,x) .


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.

Code