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Various Meanings of the Fourier Transform 📂Fourier Analysis

Various Meanings of the Fourier Transform

The Fourier transform is widely treated across various fields such as mathematics, physics, and engineering, and thus it comes to have different meanings depending on the perspective from which it is viewed. Here, its meanings in the context of mathematics, quantum mechanics, and signal processing are introduced. Let’s first define the Fourier transform and inverse transform, as they are defined in various forms in this document.

f^(ξ):=f(t)eiξxdx \hat{f}(\xi) := \int_{-\infty}^{\infty} f(t) e^{-i\xi x}dx

In Mathematics

In mathematics, the Fourier transform is fundamentally an integral transform with a kernel of eiξxe^{-i\xi x}. Since the inner product in function spaces is defined by integration, the Fourier transform of ff can be thought of as the inner product of ff and eiξxe^{i\xi x}.

f^(ξ)=f,eiξx \begin{equation} \hat{f}(\xi) = \langle f, e^{i\xi x} \rangle \end{equation}

As will be explained below, the reason why we can know the frequency ξ\xi contained in signal ff when obtaining the Fourier transform of ff is due to this meaning. Moreover, a bit more meaning can be given to kernel eiξxe^{i \xi x}. Consider the Laplacian as a linear operator.

Δϕ=2ϕ=λϕ \Delta \phi = \nabla ^{2} \phi = \lambda \phi

The λ\lambda that satisfies the above equation is called the eigenvalue of the Laplacian, and ϕ\phi is the eigenvector corresponding to λ\lambda. Functions that yield themselves upon being differentiated twice are exponential functions eiξxe^{i\xi x}. Hence, the following equation holds.

2eiξx=(ξ2)eiξx \nabla ^{2} e^{i\xi x} = (-\xi^{2}) e^{i\xi x}

Therefore, eiξxe^{i\xi x} is an eigenvector of the Laplacian, and (1)(1) can be described as follows.

Fourier transform of ff == Inner product of ff and the eigenvector of the Laplacian

In graph signal processing, the graph Fourier transform is defined based on the above interpretation.

In Signal Processing

The Fourier series of ff refers to the expansion of ff as a series of exponential functions as follows.

f(t)=ω=cωeiωt f(t) = \sum \limits_{\omega=-\infty}^{\infty} c_{\omega}e^{i\omega t}

Then, due to the [Euler’s formula], eiωt=cos(ωt)+isin(ωt)e^{i \omega t} = \cos (\omega t) + i \sin (\omega t) holds, so tt represents time, and ω\omega represents the frequency of the wave (which is the same as the oscillation frequency). However, as explained above, the Fourier transform of ff is the same as taking the inner product of ff and eiωte^{i\omega t}. Since exponential functions with different frequencies ω\omega and ω\omega^{\prime} are orthogonal to each other, taking the inner product of ff with eiωte^{i \omega t} makes all terms with different frequencies eiωte^{-i \omega^{\prime} t} become 00, leaving only the coefficient of eiωte^{i \omega t}.

f^(ω)=f,eiξx=ω=cξeiωt=cω2 \begin{equation} \hat{f}(\omega) = \langle f, e^{i\xi x} \rangle = \left\langle \sum \limits_{\omega=-\infty}^{\infty} c_{\xi}e^{i\omega t} \right\rangle = | c_{\omega} |^{2} \label{signalprocess} \end{equation}

Therefore, if we calculate the Fourier transform of ff f^(ω)\hat{f}(\omega) and find that f^(ω)0\hat{f}(\omega) \ne 0 is ω\omega, this means that ω\omega is exactly one of the signals contained in signal ff. For instance, let’s say signal ff is as follows.

f(t)=2sin(2π50t)+1.7sin(2π100t)+0.3cos(2π200t)+4cos(2π300t) f(t) = 2\sin (2\pi 50t) + 1.7\sin (2\pi 100t) + 0.3 \cos (2\pi 200t) + 4\cos(2\pi 300 t)

Fourier.png

If you calculate f^\hat{f}, you will see below picture, and you can confirm that the values of the functions at the frequencies that make up ff are not 00.

Fourier2.png

Therefore, the Fourier transform can be thought of as a tool that allows us to view a certain signal ff in both time and frequency domains.

In Quantum Mechanics

In quantum mechanics, the motion of small particles is described by the Schrödinger equation and wave functions. A wave function with a wave number of kk and an angular frequency of ω\omega is expressed as follows depending on the position and time.

ψ(x,t)=eikxωt \psi (x,t) = e^{i kx -\omega t}

However, according to the de Broglie relations, the wave number and momentum satisfy k=pk = \dfrac{p}{\hbar}, and the energy and angular frequency satisfy ω=E\omega = \dfrac{E}{\hbar}, so the wave function is as follows.

ψ(x,t)=ei(pxEt) \psi (x,t) = e^{\frac{i}{\hbar} (px - Et)}

Therefore, applying the above explanations, the wave function can move back and forth between momentum-position domains and energy-time domains by the Fourier transform. In other words, the Fourier transform is a tool that allows us to view the wave function from the two perspectives of momentum and position (energy and time).