Fast Fourier Transform (FFT)
Definition ( Piecewise
Continuous ). The function is
piecewise continuous on the closed
interval , if
there exists values with such
that f is continuous in each of the open intervals , for and
has left-hand and right-hand limits at each of the values , for .
Definition ( Fourier
Series ). If is
periodic with period and
is piecewise continuous on , then
the Fourier Series for is
,
where the coefficients are
given by the so-called Euler's formulae:
,
and
.
Theorem (Fourier Expansion). Assume
that is
the Fourier Series for . If are
piecewise continuous on , then is
convergent for all .
The relation holds
for all
where is
continuous. If is
a point of discontinuity of , then
,
where denote
the left-hand and right-hand limits, respectively. With this understanding, we
have the Fourier Series expansion:
.
Definition (Fourier Polynomial). If is
periodic with period and
is piecewise continuous on , then
the Fourier Polynomial for of
degree m is
,
where the coefficients are
given by the so-called Euler's formulae:
,
and
.
Numerical Integration calculation for the Fourier
trigonometric polynomial.
Assume that is
periodic with period and
is piecewise continuous on ,
we shall construct the Fourier trigonometric polynomial over
[0,2L] of degree m.
,
There are n subintervals of equal width based
on . The
coefficients are
for .
and
for .
The construction is possible provided that .
Remark. The sums can be viewed as
numerical integration of Euler's formulae when [0,2L]
is divided into n subintervals. The trapezoidal
rule uses the weights
for both the
and
. Since
f(x) has period , it
follows that
.
This permits us to use 1 for all the weights and the summation index from .
The Fast Fourier Transform for data.
The FFT is used to find the trigonometric polynomial when only data points
are given. We will demonstrate three ways to calculate the FFT. The first
method involves computing sums, similar to "numerical integration," the second
method involves "curve fitting," the third method involves "complex numbers."
Computing the FFT with sums.
Given data points
where
and
over [0,2L]
where
for
. Also
given that
,
to that the data is periodic with period
. We
shall construct the FFT polynomial over [0,2L]
of degree m.
,
The abscissa's form n subintervals of equal
width based
on . The
coefficients are
for
and
for .
The construction is possible provided that .
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