Consider the ODE in Equation [1]:
We are looking for the function y(t) that satisfies Equation [1] above. We know that we can take
the Fourier Transform of a
Now, if you recall
the differentiation property of the Fourier Transform,
we note that derivatives in time become simple multiplication in the Frequency domain:
Hence, Equation [2] becomes:
Equation [4] is a simple algebraic equation for Y(f)! This can be easily solved.
Equation [4] can be easiliy solved for Y(f):
In general, the solution is the inverse Fourier Transform of the result in Equation [5]. For
this case though, we can take the solution farther. Recall
that the multiplication of
two functions in the time domain produces a convolution in the Fourier domain, and
correspondingly, the multiplication of two functions in the Fourier (frequency) domain
will give the convolution in the time domain. Hence, Equation [5] becomes:
Equation [6] might not look helpful, but note that we already know the inverse Fourier Transform
for the left-most inverse Fourier transform in the second line of [6]: it's one half of
the two-sided decaying exponential function.
Hence, we can start to simplify equation [6]:
... and we've just derived the solution for the differential equation [1]. Give yourselves a round
of applause.
Now for the fine print. When we went from Step 1 to Step 2, we assumed the Fourier Transform
for y(t) existed. This is a non-trivial assumption. You may recall from your differential
equations class that the solution should also contain the so-called homogeneous solution,
when g(t)=0:
The "total" solution is the sum of the solution we obtained in equation [7] and the homogeneous
solution y_h of equation [8]. So why does the homogeneous solution not come out of our method?
The answer is simple: the non-decaying exponentials of equation [8] do not have Fourier Transforms.
That is, if you try to take the Fourier Transform of exp(t) or exp(-t), you will find the
integral diverges, and hence there is no Fourier Transform. This is a very important
caveat to keep in mind.
In the next section, we'll look at applying Fourier Transforms to partial differential equations (PDEs).

Fourier Transforms can also be applied to the solution of differential equations. To introduce
this idea, we will run through an Ordinary Differential Equation (ODE) and look at how we can use
the Fourier Transform to solve a differential equation.
[Equation 1]
*function*, so why not take the fourier transform of an *equation*?
It turns out there is no reason we can't. And since the Fourier Transform
is a linear operation, the time
domain will produce an equation where each term corresponds to the a term in the frequency domain. Taking
the Fourier Transform of Equation [1], we get Equation [2]:
[Equation 2]
[Equation 3]
[Equation 4]
*This is the utility of
Fourier Transforms applied to Differential Equations: They can convert differential equations into
algebraic equations.*
[Equation 5]
[Equation 6]
[Equation 7]
[Equation 8]

Next: Partial Differential Equations

Fourier Transform Applications

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