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RE: Reassembling Fourier Transforms

  • To: mathgroup at
  • Subject: [mg48864] RE: [mg48860] Reassembling Fourier Transforms
  • From: "Florian Jaccard" <florian.jaccard at>
  • Date: Sun, 20 Jun 2004 02:39:16 -0400 (EDT)
  • Reply-to: <florian.jaccard at>
  • Sender: owner-wri-mathgroup at

Hello !

Why don't you use Interpolation ?

For example :

points = Table[{x, Random[Real, {0, 1000}]},
    {x, 0, 1000}];

c = Interpolation[points];

This function "turns a set of random values into a function"...
And c[6] will always give the same answer !





But I apologize if I didn't understand what you wanted...



-----Message d'origine-----
De : Lee Fisher [mailto:lfis at]
Envoyé : sam., 19. juin 2004 10:31
À : mathgroup at
Objet : [mg48860] Reassembling Fourier Transforms

I am trying to turn a list of points into a function, and one of the
ways I thought to do this was to use Fourier to find the frequency
components of the list, and then to Create a sum of exponentials as

f[x_] := Random[NormalDistribution[0, 1]]
rawnoise = Table[f[x], {x, 1, 1000}];
frawnoise = Fourier[rawnoise];
magrawnoise = Abs[rawnoise];
phaserawnoise = Arg[frawnoise];
c[t] := \[Sum]\+\(n = 1\)\%1000\(( .005\ magrawnoise[\([n]\)]\ E^\((I\
n\ t\  + phaserawnoise[\([n]\)])\))\);\)\)
c[t] = Re[c[t]];

I have two questions concerning this.  First, is there an easier way to
turn a set of random values into a function so that NDSolve can move
through the function and always find the same value at a given point
(i.e. c[6] will always equal .6002)?  Second, if not, what sort of
factors are necessary in adjusting the phase and magnitude so that they
match the original numbers.

I've tried doing this with much simpler inputs, such as two sine waves
(Sin[t]+Sin[2 t]) and still the output does not properly match the

Thanks for any help,

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