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for
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:
.
Proof Fast Fourier Transform Fast Fourier Transform
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
.
Animations (Fourier Series Fourier Series). Internet hyperlinks to animations.
Computer Programs Fast Fourier Transform Fast Fourier Transform
Example 1. Assume
that
is periodic with period
, i.e.
, and
is defined by
for
.
Find the Fourier polynomial of degree n = 5.
Solution
1.
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
.
Example 2. Assume
that
is periodic with period
, i.e.
, and
is defined by
for
.
Find the Fourier polynomial of degree n = 5 for the
12 equally spaced points in the
interval
.
Use the "numerical integration" method for finding the
coefficients.
Solution
2.
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
.
Remark. Notice that
the sums
involve
only
ordinates
.
Animations (Discrete Fourier series FFT Discrete Fourier series FFT). Internet hyperlinks to animations.
Example 3. Given
the 12 equally spaced data points
![]()
![]()
![]()
![]()
which can be extended periodically over
,
if we define
.
Find the Fourier polynomial of degree n = 5 for the
12 equally spaced points over
interval
.
Use numerical sums to find the coefficients.
Solution
3.
Fitting a Fourier trigonometric
polynomial to data.
The built in Mathematica Fit
subroutine can be used to perform the computation.
Caution. Do not
include both endpoints of the interval.
Example 4. Given
the 12 equally spaced data points
![]()
![]()
![]()
![]()
which can be extended periodically over
,
if we define
.
Find the Fourier polynomial of degree n = 5 for the
12 equally spaced points over
interval
.
Use Mathematica's Fit subroutine to find the coefficients.
Solution
4.
Background for using Mathematica's
FFT.
Trigonometric curve fitting at discrete
points is equivalent to finding the Fast
Fourier Transform (FFT) for a discrete data set. The
coefficients of the trigonometric polynomial can be obtained using
Mathematica's built in "Fourier" procedure
(FFT).
Caution. However,
we first we need to use that part of the period
function
defined
in the interval
. That's
the way Mathematica expects us to see it ! Be sure
to redefine
on
the interval
.
Example 5. Given
the 12 equally spaced data points
![]()
![]()
![]()
![]()
which can be extended periodically over
,
if we define
.
Find the Fourier polynomial of degree n = 5 for the
12 equally spaced points over
interval
.
Use Mathematica's built in Fourier
subroutine to find the solution.
Solution
5.
Old Lab Project (Trigonometric Polynomials-FFT Trigonometric Polynomials-FFT). Internet hyperlinks to an old lab project.
Research Experience for Undergraduates
Fast Fourier Transform Fast Fourier Transform Internet hyperlinks to web sites and a bibliography of articles.
Download this Mathematica Notebook Fast Fourier Transform
Return to Numerical Methods - Numerical Analysis
(c) John H. Mathews 2004