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📂Fourier Analysis

Definition

Fourier Transform as a Function

We define the Fourier transform of function ff \in L1L^{1} as follows:

f^(ξ):=f(t)eiξtdt \hat{f}(\xi) := \int_{-\infty}^{\infty} f(t) e^{-i \xi t}dt

Fourier Transform as an Operator

An operator defined as F:L1\mathcal{F} : L^{1} \to C0C_{0} is called the Fourier transform.

F[f](ξ)=f(t)eiξtdt \mathcal{F}[f] (\xi) = \int_{-\infty}^{\infty} f(t) e^{-i \xi t}dt

Explanation

As seen in the definition, the term Fourier transform can refer to the operator F\mathcal{F} itself as well as to the function value f^=Ff=F[f]\hat{f} = \mathcal{F}f = \mathcal{F}[f] of F\mathcal{F}. The codomain of F\mathcal{F} being C0C_{0} is guaranteed by the Riemann-Lebesgue Lemma. Additionally, it can be easily shown that the following holds true. For fL1f \in L^{1},

Fff1 \left\| \mathcal{F}f \right\|_{\infty} \le \left\| f \right\|_{1}

Proof

Ff=maxξRFf(ξ)=maxξRf(t)eiξtdtmaxξRf(t)eiξtdt=f(t)dt=f1 \begin{align*} \left\| \mathcal{F}f \right\|_{\infty} = \max\limits_{\xi \in \mathbb{R}} \left| \mathcal{F}f(\xi) \right| &= \max\limits_{\xi \in \mathbb{R}} \left| \int_{-\infty}^{\infty} f(t) e^{-i \xi t}dt \right| \\ &\le \max\limits_{\xi \in \mathbb{R}} \int_{-\infty}^{\infty} \left| f(t) e^{-i \xi t} \right| dt \\ &= \int_{-\infty}^{\infty} \left| f(t) \right| dt = \left\| f \right\|_{1} \end{align*}

The Fourier transform is a type of integral transform and its inverse transform is as follows:

f(t)=F1f^(t)=12πf^(ξ)eitξdξ f(t) = \mathcal{F}^{-1}\hat{f}(t) = \frac{1}{2\pi} \int_{-\infty}^{\infty} \hat{f}(\xi) e^{i t \xi} d \xi

The preceding constant 12π\dfrac{1}{2\pi} can be placed either before the inverse transform or before the transform since it doesn’t matter where it’s placed. Alternatively, 12π\frac{1}{\sqrt{2\pi}} can be placed on both sides. The difference in notation is merely a matter of the author’s preference and does not fundamentally affect the concept. From the definition, it is clear that the Fourier transform is well-defined if ff is integrable, i.e., satisfies the condition fL1f\in L^{1}. Also, if f^\hat{f} is integrable, the Fourier inverse transform is well-defined as well.

Fourier Transform of Multivariable Functions

The Fourier transform of a multivariable function is defined as follows. The Fourier transform of a multivariable function fL1(Rn)f \in L^{1}(\mathbb{R}^{n}) is,

Ff(ξ):=f(x)eiξxdx \mathcal{F}f(\boldsymbol{\xi}):=\int f(x)e^{-i \boldsymbol{\xi} \cdot \mathbf{x} }d\mathbf{x}

Ff(ξ1, , ξn):= ⁣f(x1, , xn)ei(ξ1x1++ξnxn)dx1dxn \mathcal{F} f(\xi_{1},\ \cdots ,\ \xi_{n}) := \int_{-\infty}^{\infty} \dots \int_{-\infty}^{\infty} f(x_{1},\ \cdots,\ x_{n})e^{-i(\xi_{1} x_{1}+\cdots+\xi_{n} x_{n})}dx_{1}\cdots dx_{n}

Notation

There are two commonly used notations for the Fourier transform of ff.

F(f),f^ \mathcal{F}(f),\quad \hat{f}

Textbooks often use different symbols depending on the author’s preference. Though the hat notation on the right seems convenient, it can cause confusion, so it is preferable to use the notation on the left for clarity. For example, if the input function symbol is lengthy, using the hat notation can be confusing or less visually appealing. In such cases, using F\mathcal{F} clearly and precisely conveys the meaning of the equation. For instance, the Fourier transform of WcfW_{c}f is better represented as F\mathcal{F}, as shown below.

F(Wcf),Wcf^,Wcf^ \mathcal{F}(\mathcal{W}_{c}f),\quad \hat{\mathcal{W}_{c}f},\quad \widehat{\mathcal{W}_{c}f}

However, when there is no potential for confusion, the hat notation is more convenient. Similarly, having multiple notations for the same concept also occurs with differentiation.

f,dfdx f^{\prime}, \quad \dfrac{df}{dx}

The advantages and disadvantages of the notations f^\hat{f} and F\mathcal{F} resemble those of the Newton notation and the Leibniz notation in differentiation. The Newton notation is advantageous in terms of efficiency and convenience, whereas the Leibniz notation excels in precision and clarity when calculating chain rules, for instance.

Derivation1

A function with a finite interval (i.e., defined on a finite interval) can be approximated using the Fourier series. While this is useful, it can only be applied to periodic functions, thus necessitating a tool for non-periodic functions. This led to the development of the Fourier transform. The key idea in deriving the Fourier transform is to consider a non-periodic function as if it were a periodic function with a period spanning the entire real line, repeating once over the entire number line.

Let ff be a function defined on the interval [L,L)[-L,L). Then, the Fourier series and complex Fourier coefficients of ff are as follows.

f(t)=n=cneinπtL \begin{equation} f(t)=\sum \limits_{n=-\infty}^{\infty} c_{n} e^{i\frac{n\pi t}{L}} \end{equation}

cn=12LLLf(t)einπtLdt c_{n} = \dfrac{1}{2L}\int_{-L}^{L}f(t)e^{-i\frac{n \pi t}{L} }dt

Let us perform the following variable substitution.

Δξ=πL,ξn=nΔξ=nπL \Delta \xi = \dfrac{\pi}{L},\quad \xi_{n}=n\Delta\xi=\dfrac{n\pi}{L}

Then, (1)(1) is as follows.

f(t)=n=cneiξnt,cn=12LLLf(t)eiξntdt f(t) = \sum \limits_{n=-\infty}^{\infty} c_{n} e^{i\xi_{n} t}, \quad c_{n} = \dfrac{1}{2L}\int_{-L}^{L}f(t)e^{-i \xi_{n} t }dt

Multiplying f(t)f(t) by an appropriate constant and denoting the integral of cnc_{n} as f^(ξn)\hat{f}(\xi_{n}),

f(t)=Lπn=cneiξntΔξ,cn=12Lf^(ξn) f(t)=\dfrac{L}{\pi}\sum \limits_{n=-\infty}^{\infty} c_{n} e^{i\xi_{n} t}\Delta \xi , \quad c_{n} = \dfrac{1}{2L}\hat{f}(\xi_{n})

Assuming that t±t \rightarrow \pm \infty converges quickly to 00 as f(t)f(t) approaches t±t \rightarrow \pm \infty, it would not significantly alter the original cnc_{n} if we extend the integration interval from [L,L)[-L,L) to (,)(-\infty,\infty).

cn12Lf(t)eiξntdt c_{n} \approx \dfrac{1}{2L} \int_{-\infty}^{\infty} f(t) e^{-i\xi_{n} t}dt

This is a function of ξn\xi_{n} only, so denoting it as cn=12Lf^(ξn)c_{n} = \frac{1}{2L}\hat{f}(\xi_{n}), substituting it into f(t)f(t),

f(t)12πn=f^(ξn)eiξntΔξ f(t) \approx \dfrac{1}{2 \pi}\sum \limits_{n=-\infty}^{\infty} \hat{f}(\xi_{n}) e^{i\xi_{n} t}\Delta \xi

This closely resembles a Riemann sum. Taking the limit LL\rightarrow \infty and the resulting Δξ0\Delta\xi \rightarrow 0, the sum turns into an integral and the expression becomes \approx, which is an identity.

f(t)=12πf^(ξ)eiξtdξandf^(ξ)=f(t)eiξtdt f(t) = \dfrac{1}{2 \pi}\int_{-\infty}^{\infty} \hat{f}(\xi) e^{i\xi t} d\xi \quad \text{and} \quad \hat{f}(\xi)=\int_{-\infty}^{\infty} f(t) e^{-i\xi t}dt

Here, denoting f^\hat{f} as the Fourier transform of ff, we refer to ff as the Fourier inverse transform of f^\hat{f}.

See Also


  1. Gerald B. Folland, Fourier Analysis and Its Applications (1992), p204-205 ↩︎