logo

Sampling Theorem 📂Fourier Analysis

Sampling Theorem

Buildup[^1]

Consider a physical signal ff being measured over time t1<t2<t3<t_{1} < t_{2} < t_{3} < \cdots. Even if we know f(t1),f(t2),f(t_{1}), f(t_{2}), \dots, we generally cannot know the values for arbitrary f(t)f(t). However, let’s assume that signal ff contains only frequencies within a certain range. That is, we consider a signal ff that contains only frequencies smaller than some constant Ω\Omega, which is referred to as a band-limited signal.

In the language of Fourier analysis, this is the same as saying that the function values are all 00 in the region where f^(ω)\hat{f}(\omega) is ωΩ|\omega| \ge \Omega. Therefore, the condition that signal ff is band-limited is equivalent to the condition f^(ω)=0 for ωΩ\hat{f} (\omega) = 0\ \text{for } | \omega | \ge \Omega, meaning f^L1\hat{f} \in L^{1}. Under such conditions, the following powerful theorem holds.

Theorem

Assuming that fL2f\in L^{2} and f^(ω)=0 for ωΩ\hat{f} (\omega) = 0\ \text{for } | \omega | \ge \Omega, then f(t)f(t) is determined by the values in nπ/Ω(n=0,±1,±2,)n\pi / \Omega (n=0, \pm 1, \pm 2, \dots). That is, the following applies.

f(t)=n=f(nπΩ)sin(Ωtnπ)Ωtnπ f(t) = \sum \limits_{n = -\infty}^{\infty} f \left( \dfrac{n\pi}{\Omega}\right) \dfrac{\sin (\Omega t -n\pi )}{\Omega t - n\pi}

Explanation

This is referred to as the sampling theorem. The sampling theorem provides the condition under which all f(t)f(t) for all tt can be determined using a countable number of function values f(nπΩ)f \left( \dfrac{n\pi}{\Omega}\right).

From the perspective of signal analysis, the condition f^(ω)=0 for ωΩ\hat{f} (\omega) = 0\ \text{for } | \omega | \ge \Omega means that the frequency of signal ff is limited.

Also, a similar formula applies to the frequency function f^L2\hat{f} \in L^{2} and time-limited signal f(t)f(t).

Frequency Sampling Theorem

Assume that f^L2\hat{f} \in L^{2} and f(t)=0 for tLf (t) = 0\ \text{for } | t | \ge L. Then f^(ω)\hat{f}(\omega) is determined by the values in nπ/L(n=0,±1,±2,)n\pi / L(n=0, \pm 1, \pm 2, \dots). That is, the following applies.

f^(ω)=n=f^(nπL)sin(Lωnπ)Lωnπ \hat{f}(\omega) = \sum \limits_{n = -\infty}^{\infty} \hat{f} \left( \dfrac{n\pi}{L}\right) \dfrac{\sin (L \omega -n\pi )}{L \omega - n\pi}

The proof is similar to that of the time sampling theorem.

Proof

Since f^L1\hat{f} \in L^{1}, f^\hat{f} can be expressed as a Fourier series. f^(ω)\hat{f} (\omega) is defined at [Ω,Ω][-\Omega, \Omega], so the complex Fourier series is as follows.

f^(ω)=cneinπω/Ω(ωΩ) \begin{equation} \hat{f}(\omega)=\sum_{-\infty}^{\infty} c_{-n} e^{-i n \pi \omega / \Omega} \quad(|\omega| \leq \Omega) \label{eq1} \end{equation}

For convenience in the proof process, nn is denoted by n-n. The coefficient cnc_{-n} is as follows.

cn=12ΩΩΩf^(ω)einπω/Ωdω=12Ωf^(ω)einπω/Ωdω=πΩ12πf^(ω)eiω(nπ/Ω)dω \begin{align*} c_{-n} &= \dfrac{1}{2 \Omega} \int_{-\Omega}^{\Omega} \hat{f}(\omega) e^{i n \pi \omega / \Omega} d \omega \\ &= \dfrac{1}{2 \Omega} \int_{-\infty}^{\infty} \hat{f}(\omega) e^{i n \pi \omega / \Omega} d \omega \\ &= \dfrac{\pi}{\Omega} \dfrac{1}{2\pi} \int_{-\infty}^{\infty} \hat{f}(\omega) e^{i \omega (n \pi / \Omega)} d\omega \end{align*}

Since f^(ω)=0 for ωΩ\hat{f} (\omega) = 0\ for\ | \omega | \ge \Omega, then f^(ω)L2\hat{f} (\omega) \in L^{2}, and by the Fourier inverse transform theorem, the following applies.

f(t)=12πf^(ω)eiωtdω \begin{equation} f(t) =\dfrac{1}{2\pi} \int _{-\infty} ^{\infty}\hat{f}(\omega) e^{i\omega t}d\omega \label{eq2} \end{equation}

Therefore, one obtains the following equation.

cn=πΩ12πf^(ω)eiω(nπ/Ω)dω=πΩf(nπΩ) \begin{align*} c_{-n} &= \dfrac{\pi}{\Omega} \dfrac{1}{2\pi} \int_{-\infty}^{\infty} \hat{f}(\omega) e^{i \omega (n \pi / \Omega)} d\omega \\ &= \dfrac{\pi}{\Omega} f \left( \dfrac{n\pi}{\Omega}\right) \end{align*}

Inserting this into (eq1)\eqref{eq1} yields the following.

f^(ω)=cneinπω/Ω(ωΩ)=πΩf(nπΩ)einπω/Ω(ωΩ) \hat{f}(\omega) = \sum_{-\infty}^{\infty} c_{-n} e^{-i n \pi \omega / \Omega} \quad(|\omega| \leq \Omega) = \sum_{-\infty}^{\infty} \dfrac{\pi}{\Omega} f \left( \dfrac{n\pi}{\Omega}\right) e^{-i n \pi \omega / \Omega} \quad(|\omega| \leq \Omega)

Again inserting this into (eq2)\eqref{eq2} yields the equation below.

f(t)=12πf^(ω)eiωtdω=12πΩΩf^(ω)eiωtdω=12ΩΩΩf(nπΩ)einπω/Ωeiωtdω \begin{align*} f(t) &= \frac{1}{2 \pi} \int_{-\infty}^{\infty} \hat{f}(\omega) e^{i \omega t} d \omega = \frac{1}{2 \pi} \int_{-\Omega}^{\Omega} \hat{f}(\omega) e^{i \omega t} d \omega \\ &=\frac{1}{2 \Omega} \int_{-\Omega}^{\Omega} \sum_{-\infty}^{\infty} f\left(\frac{n \pi}{\Omega}\right) e^{-i n \pi \omega / \Omega} e^{i \omega t} d \omega \end{align*}

In the function space, the inner product is defined as a definite integral, and since the inner product is continuous, the limit can be taken out, so the equation is as follows.

f(t)=12ΩΩΩf(nπΩ)einπω/Ωeiωtdω=12Ωf(nπΩ)einπω/Ω,eiωt=12Ωf(nπΩ)einπω/Ω,eiωt=12ΩΩΩf(nπΩ)einπω/Ωeiωtdω=12Ωf(nπΩ)ΩΩeinπω/Ωeiωtdω \begin{align*} f(t) &= \frac{1}{2 \Omega} \int_{-\Omega}^{\Omega} \sum_{-\infty}^{\infty} f\left(\frac{n \pi}{\Omega}\right) e^{-i n \pi \omega / \Omega} e^{i \omega t} d \omega \\ &= \frac{1}{2 \Omega} \left\langle \sum_{-\infty}^{\infty} f\left(\frac{n \pi}{\Omega}\right) e^{-i n \pi \omega / \Omega}, e^{-i \omega t} \right\rangle \\ &= \frac{1}{2 \Omega} \sum_{-\infty}^{\infty} \left\langle f\left(\frac{n \pi}{\Omega}\right) e^{-i n \pi \omega / \Omega}, e^{-i \omega t} \right\rangle \\ &= \frac{1}{2 \Omega} \sum_{-\infty}^{\infty} \int_{-\Omega}^{\Omega} f\left(\frac{n \pi}{\Omega}\right) e^{-i n \pi \omega / \Omega} e^{i \omega t} d \omega \\ &= \frac{1}{2 \Omega} \sum_{-\infty}^{\infty} f\left(\frac{n \pi}{\Omega}\right) \int_{-\Omega}^{\Omega} e^{-i n \pi \omega / \Omega} e^{i \omega t} d \omega \end{align*}

Calculating the integral above yields the following.

ΩΩeinπω/Ωeiωtdω=ΩΩei(Ωtnπ)ω/Ωdω=ei(Ωtnπ)ω/Ωi(Ωtnπ)/ΩΩΩ=1i(Ωtnπ)/Ω[ei(Ωtnπ)ei(Ωtnπ)]=2(Ωtnπ)/Ωei(Ωtnπ)ei(Ωtnπ)2i=2sin(Ωtnπ)(Ωtnπ)/Ω \begin{align*} \int_{-\Omega}^{\Omega} e^{-i n \pi \omega / \Omega} e^{i \omega t} d \omega &= \int_{-\Omega}^{\Omega} e^{i(\Omega t- n \pi )\omega/\Omega} d \omega \\ &= \left. \frac{e^{i(\Omega t-n \pi) \omega / \Omega}}{i(\Omega t-n \pi) / \Omega}\right|_{-\Omega} ^{\Omega} \\ &= \frac{1}{i(\Omega t-n \pi) / \Omega}\left[ e^{i(\Omega t-n \pi)} - e^{-i(\Omega t-n \pi)} \right] \\ &= \frac{2}{(\Omega t-n \pi) / \Omega}\dfrac{ e^{i(\Omega t-n \pi)} - e^{-i(\Omega t-n \pi)}}{2i} \\ &= \frac{2 \sin (\Omega t-n \pi)}{(\Omega t-n \pi) / \Omega} \end{align*}

Substituting and rearranging yields the following.

f(t)=12Ωf(nπΩ)ΩΩeinπω/Ωeiωtdω=12Ωf(nπΩ)2sin(Ωtnπ)(Ωtnπ)/Ω=f(nπΩ)2sin(Ωtnπ)Ωtnπ \begin{align*} f(t) &= \frac{1}{2 \Omega} \sum_{-\infty}^{\infty} f\left(\frac{n \pi}{\Omega}\right) \int_{-\Omega}^{\Omega} e^{-i n \pi \omega / \Omega} e^{i \omega t} d \omega \\ &= \frac{1}{2 \Omega} \sum_{-\infty}^{\infty} f\left(\frac{n \pi}{\Omega}\right) \frac{2 \sin (\Omega t-n \pi)}{(\Omega t-n \pi) / \Omega} \\ &= \sum_{-\infty}^{\infty} f\left(\frac{n \pi}{\Omega}\right) \frac{2 \sin (\Omega t-n \pi)}{\Omega t-n \pi} \end{align*}