Finding Fourier Coefficients of Continuous Function

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The Fourier transform is an integral transform widely used in physics and engineering. They are widely used in signal analysis and are well-equipped to solve certain partial differential equations.

The convergence criteria of the Fourier transform (namely, that the function be absolutely integrable on the real line) are quite severe due to the lack of the exponential decay term as seen in the Laplace transform, and it means that functions like polynomials, exponentials, and trigonometric functions all do not have Fourier transforms in the usual sense. However, we can make use of the Dirac delta function to assign these functions Fourier transforms in a way that makes sense.

Because even the simplest functions that are encountered may need this type of treatment, it is recommended that you be familiar with the properties of the Laplace transform before moving on. Furthermore, it is more instructive to begin with the properties of the Fourier transform before moving on to more concrete examples.

Preliminaries

1. 1

   Determine the Fourier transform of a derivative. A simple integration by parts, coupled with the observation that ${\displaystyle f(t)}$ must vanish at both infinities, yields the answer below.^[4]

2. 2

   Determine the Fourier transform of a function multiplied by $$ t n {\displaystyle t^{n}} . The symmetry of the Fourier transform gives the analogous property in frequency space. We will first work with ${\displaystyle n=1}$ and then generalize.

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5. 5

   Determine the Fourier transform of a stretched function $$ f ( c t ) {\displaystyle f(ct)} . The stretch property seen in the Laplace transform also has an analogue in the Fourier transform.

   • ${\displaystyle {\begin{aligned}{\mathcal {F}}\{f(ct)\}&=\int _{-\infty }^{\infty }f(ct)e^{-i\omega t}\mathrm {d} t,\quad u=ct\\&={\frac {1}{|c|}}\int _{-\infty }^{\infty }f(u)e^{-i\omega u/c}\mathrm {d} u\\&={\frac {1}{|c|}}{\hat {f}}\left({\frac {\omega }{c}}\right)\end{aligned}}}$

6. 6

   Determine the Fourier transform of a convolution of two functions. As with the Laplace transform, convolution in real space corresponds to multiplication in the Fourier space.^[7]

   • ${\displaystyle {\begin{aligned}{\mathcal {F}}\{f(t)*g(t)\}&=\int _{-\infty }^{\infty }e^{-i\omega t}\mathrm {d} t\int _{-\infty }^{\infty }f(t-y)g(y)\mathrm {d} y,\quad u=t-y\\&=\int _{-\infty }^{\infty }e^{-i\omega (u+y)}\mathrm {d} u\int _{-\infty }^{\infty }f(u)g(y)\mathrm {d} y\\&=\int _{-\infty }^{\infty }f(u)e^{-i\omega u}\mathrm {d} u\int _{-\infty }^{\infty }g(y)e^{-i\omega y}\mathrm {d} y\\&={\hat {f}}(\omega ){\hat {g}}(\omega )\end{aligned}}}$

7. 7

   Determine the Fourier transform of even and odd functions. Even and odd functions have particular symmetries. We arrive at these results using Euler's formula and understanding how even and odd functions multiply. ^[8]

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1. 1

   Substitute the function into the definition of the Fourier transform. As with the Laplace transform, calculating the Fourier transform of a function can be done directly by using the definition. We will use the example function ${\displaystyle f(t)={\frac {1}{t^{2}+1}},}$ which definitely satisfies our convergence criteria.^[9]

   • ${\displaystyle {\mathcal {F}}\left\{{\frac {1}{t^{2}+1}}\right\}=\int _{-\infty }^{\infty }{\frac {e^{-i\omega t}}{t^{2}+1}}\mathrm {d} t}$

2. 2

   Evaluate the integral using any means possible. This integral resists the techniques of elementary calculus, but we can make use of residue theory instead.^[10]

   • To use residues, we create a contour ${\displaystyle \gamma }$ consisting of a concatenation of the real line and a semicircular arc in the lower half plane that circles clockwise. The goal is to show that the real integral equals the contour integral by showing that the arc integral vanishes.
     • ${\displaystyle \oint _{\gamma }{\frac {e^{-i\omega t}}{t^{2}+1}}\mathrm {d} t=\int _{-\infty }^{\infty }{\frac {e^{-i\omega t}}{t^{2}+1}}\mathrm {d} t+\int _{\text{arc}}{\frac {e^{-i\omega t}}{t^{2}+1}}\mathrm {d} t}$
   • We may factor the denominator to show that the function has simple poles at ${\displaystyle t_{\pm }=\pm i.}$ Since only ${\displaystyle t_{-}}$ is being enclosed, we can use the residue theorem to calculate the value of the contour integral.
     • ${\displaystyle \operatorname {Res} (f(t);-i)={\frac {e^{-\omega }}{-2i}}}$
   • Note that since our contour is in the clockwise direction, there is an additional negative sign.
     • ${\displaystyle \oint _{\gamma }{\frac {e^{-i\omega t}}{t^{2}+1}}\mathrm {d} t=-2\pi i\cdot {\frac {e^{-\omega }}{-2i}}=\pi e^{-\omega }}$
   • Equally important is the process in showing that the arc integral vanishes. Jordan's lemma aids in this evaluation. While the lemma does not say that the integral vanishes, it does bound the difference between the contour integral and the real integral.^[11] We apply the lemma to the lower half plane below for a function ${\displaystyle f(t)=e^{-i\omega t}g(t),}$ where ${\displaystyle \omega >0.}$ Given a parameterization ${\displaystyle C=Re^{-i\phi }}$ where ${\displaystyle \phi \in [0,\pi ],}$ then Jordan's lemma prescribes the following bound of the integral:
     • ${\displaystyle {\Bigg |}\int _{C}f(t)\mathrm {d} t{\Bigg |}\leq {\frac {\pi }{\omega }}\max _{\phi \in [0,\pi ]}g(Re^{-i\phi })}$
   • Now, all we need to do is show that ${\displaystyle g(t)}$ vanishes in the large ${\displaystyle R}$ limit, which is trivial here because the function falls off as ${\displaystyle 1/R^{2}.}$
     • ${\displaystyle \lim _{R\to \infty }{\frac {1}{(Re^{-i\phi })^{2}+1}}=0}$
   • What is the domain of ${\displaystyle \omega }$ in this result? As stated previously, Jordan's lemma only applies for ${\displaystyle \omega >0.}$ However, when one repeats this calculation by enclosing the upper half plane, finding the residue at the other pole, and applying Jordan's lemma again to ensure the arc integral vanishes, the result will be ${\displaystyle \pi e^{\omega }}$ while the domain of ${\displaystyle \omega }$ will be the negative reals. So the final answer is written below.
     • ${\displaystyle {\mathcal {F}}\left\{{\frac {1}{t^{2}+1}}\right\}=\pi e^{-|\omega |}}$

3. 3

   Evaluate the Fourier transform of the rectangular function. The rectangular function ${\displaystyle \operatorname {rect} (t),}$ or the unit pulse, is defined as a piecewise function that equals 1 if ${\displaystyle -{\frac {1}{2}}<t<{\frac {1}{2}},}$ and 0 everywhere else. As such, we can evaluate the integral over just these bounds. The result is the cardinal sine function.

4. 4

   Evaluate the Fourier transform of the Gaussian function. The Gaussian function is one of the few functions that is its own Fourier transform. We integrate by completing the square.^[12]

   • ${\displaystyle {\begin{aligned}{\mathcal {F}}\{e^{-t^{2}}\}&=\int _{-\infty }^{\infty }e^{-t^{2}}e^{-i\omega t}\mathrm {d} t\\&=\int _{-\infty }^{\infty }e^{-(t^{2}+i\omega t-\omega ^{2}/4+\omega ^{2}/4)}\mathrm {d} t\\&=e^{-\omega ^{2}/4}\int _{-\infty }^{\infty }e^{-(t+i\omega /2)^{2}}\mathrm {d} t\\&={\sqrt {\pi }}e^{-\omega ^{2}/4}\end{aligned}}}$

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1. 1

   Evaluate the Fourier transform of $$ e i a t {\displaystyle e^{iat}} . If you have had some exposure to Laplace transforms before, you know that the exponential function is the "simplest" function that has a Laplace transform. In the case of the Fourier transform, this function is not well-behaved because the modulus of this function does not tend to 0 as ${\displaystyle t\to \infty .}$ Nevertheless, its Fourier transform is given as the delta function.

2. 2

   Evaluate the Fourier transform of $$ t n e i a t {\displaystyle t^{n}e^{iat}} . We can use the shift property to compute Fourier transforms of powers, and therefore all polynomials. Note that this involves computing derivatives of the delta function.

   • ${\displaystyle {\mathcal {F}}\{t^{n}e^{iat}\}=2\pi i^{n}{\frac {\mathrm {d} ^{n}}{\mathrm {d} \omega ^{n}}}\delta (\omega -a)}$

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• There are two other commonly used conventions for the Fourier transform.

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