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Re: minimax polynomial determination

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  • Subject: [mg115770] Re: minimax polynomial determination
  • From: Leslaw Bieniasz <nbbienia at>
  • Date: Thu, 20 Jan 2011 06:30:27 -0500 (EST)
  • References: <ih6ee9$3gb$>

On Wed, 19 Jan 2011, Bill Rowe wrote:

> On 1/18/11 at 5:48 AM, nbbienia at (Leslaw Bieniasz)
> wrote:
>> I need to determine minimax polynomial approximations to a certain
>> function computed using MATHEMATICA. Unfortunately it is not
>> possible to calculate exact derivatives of the function. Is there
>> any way to use the MiniMaxApproximation[] algorithm with numerically
>> approximated derivatives? I would appreciate an example.
> A minmax approximation can be efficiently computed as a
> Chebyshev series. You don't need to compute the derivative to
> get the coefficients for a Chebyshev series. All you need do is
> sample the function at appropriate points. Then the needed
> coefficients can be computed using a discrete cosine transform.
> See the applications section of ref/FourierDCT for details of
> how to sample the function correctly and use FourierDCT to
> compute the needed coefficients.

Sorry, I don't grasp that. Minimax polynomial results from the 
minimisation of the norm maximum of the difference between
the polynomial and a given function. Therefore, some optimisation
procedure must be used (often the Remez algorithm is used for this 
purpose). It seems that the MiniMaxAlgorithm implemented in MATHEMATICA
needs exact derivatives to perform the minimisation. I don't see how the
minimax polynomial could be found without minimisation.
I can imagine, however, that the minimisation can be performed
without using the derivative information, or by using approximate
derivatives. So, my question was if one can use somehow the
approximate derivatives with the MiniMaxAlgorithm.


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