remez - Maple Help
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numapprox

  

remez

  

Remez algorithm for minimax rational approximation

 

Calling Sequence

Parameters

Description

Examples

Calling Sequence

remez(w, f, a, b, m, n, crit, 'maxerror')

Parameters

w

-

procedure representing a weight function w(x) > 0 on [a, b]

f

-

procedure representing the function f(x) to be approximated

a, b

-

numeric values specifying the interval [a, b]

m

-

integer specifying the desired degree of the numerator

n

-

integer specifying the desired degree of the denominator

crit

-

Array indexed  containing an initial estimate of the critical set (i.e. the points of max/min of the error curve)

maxerror

-

name which will be assigned the minimax norm of

Description

• 

This is not usually invoked as a user-level routine.  See numapprox[minimax] for the standard user interface to the Remez algorithm.

• 

This procedure computes the best minimax rational approximation of degree  for a given real function f(x) on the interval [a, b] with respect to the positive weight function w(x).

• 

Specifically, it computes the rational expression r(x) such that

(1)

  

is minimized over all rational expressions  with numerator of degree m and denominator of degree n.

• 

The value returned is an operator r such that  is the desired approximation as a quotient of polynomials in Horner (nested multiplication) form.

• 

Note that if f(x) is nonzero on the interval of approximation then the relative error will be minimized by specifying the weight function .

• 

If  then the best minimax polynomial approximation of degree m is computed.

• 

The last argument 'maxerror' must be a name and upon return, its value will be an estimate of the minimax norm specified by equation (1) above.

• 

Various levels of user information will be displayed during the computation if infolevel[remez] is assigned values between 1 and 3.

• 

The command with(numapprox,remez) allows the use of the abbreviated form of this command.

Examples

w := proc(x) 1.0 end proc:

f := proc(x) evalf(exp(x)) end proc:

(1)

(2)

(3)

g := proc(x) if x=0 then 1.0 else evalf(tan(x)/x) end if end proc:

(4)

(5)

See Also

numapprox[minimax]

 


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