Operations

  • the most fundamental question of signal processing

    • how to use one signal (function) to modify another

    • most often: to modify the spectrum of the signal

  • convolution is probably the most important operation in signal processing

Linear Combination

\[\mathcal{F}(a \cdot f + b \cdot g) = a \cdot \mathcal{F}f + b \cdot \mathcal{F}g\]

Can be proved by applying definition directly.

Shift

  • Shift in time (signal) corresponds to phase shift in frequency (FT)

\[(\mathcal{F} f(t - b))(s) = e^{-2 \pi i s b} \cdot \mathcal{F} f (s)\]

Proof:

\[ \begin{align}\begin{aligned}(\mathcal{F} f(t - b))(s) = \int_{-\infty}^{+\infty} e^{-2 \pi i s t} f(t - b) dt\\\begin{split}\\\end{split}\\Let: u = t - b \implies t = u + b\\\begin{split}\\\end{split}\\\begin{split}(\mathcal{F} f(t - b))(s) & = \int_{-\infty}^{+\infty} e^{-2 \pi i s \cdot (u + b)} f(u) du \\ & = e^{-2 \pi i s b} \int_{-\infty}^{+\infty} e^{-2 \pi i s u} f(u) du \\ & = e^{-2 \pi i s b} \cdot \mathcal{F} f (s)\end{split}\end{aligned}\end{align} \]
\[\tag*{$\blacksquare$}\]

Stretch

  • squashed in time (signal) corresponds to stretched in phase and squashed in magnitude

  • stretched in time (signal) corresponds to squeezed in phase and stretched in magnitude

  • a signal cannot be both localized in time and frequency

\[(\mathcal{F} f(a t))(s) = |\frac{1}{a}| F(\frac{s}{a})\]

Proof:

\[ \begin{align}\begin{aligned}(\mathcal{F} f(a t))(s) = \int_{-\infty}^{+\infty} e^{-2 \pi i s t} f(at) dt\\\begin{split}\\\end{split}\\Let: u = a t \implies t = \frac{1}{a} u\\\begin{split}\\\end{split}\\\begin{split}(\mathcal{F} f(a t))(s) & = \int_{-\infty}^{+\infty} e^{-2 \pi i s \cdot \frac{u}{a}} f(u) dt \\ & = \int_{-\infty}^{+\infty} e^{-2 \pi i \cdot \frac{s}{a} \cdot u} f(u) dt \\ & = |\frac{1}{a}| \int_{-\infty}^{+\infty} e^{-2 \pi i \cdot \frac{s}{a} \cdot u} f(u) du \\ & = |\frac{1}{a}| F(\frac{s}{a})\end{split}\end{aligned}\end{align} \]
\[\tag*{$\blacksquare$}\]

Differentiation

Fourier transform turns differentiation into multiplication.

The Derivitive Theorem of Fourier Transform:

\[ \begin{align}\begin{aligned}\mathcal{F} f^{(n)} & = (2 \pi i s)^n \cdot \mathcal{F} f\\\begin{split}\\\end{split}\\\frac{\partial^n \mathcal{F} f}{\partial s^n} & = \mathcal{F} ((-2 \pi i x)^n f(x))\end{aligned}\end{align} \]

Rigorous proof can be found in Differentiation Formulas.

Warning

These formulas hold only if function \(f\) satisfies some specific conditions e.g. vanish at infinity

Convolution

Convolution Theorem of Fourier Transform:

First statement:

\[ \begin{align}\begin{aligned}\mathcal{F} f \cdot \mathcal{F} g = \mathcal{F}(f * g)\\\begin{split}\\\end{split}\\\mathcal{F}^{-1} F \cdot \mathcal{F}^{-1} G = \mathcal{F}^{-1} (F * G)\end{aligned}\end{align} \]

Second statement:

\[ \begin{align}\begin{aligned}\mathcal{F} (f \cdot g) = \mathcal{F} f * \mathcal{F} g\\\begin{split}\\\end{split}\\\mathcal{F}^{-1} (F \cdot G) = \mathcal{F}^{-1} F * \mathcal{F}^{-1} G\end{aligned}\end{align} \]

Proof:

\[ \begin{align}\begin{aligned}\begin{split}\mathcal{F} g(s) \cdot \mathcal{F} f(s) & = \int_{-\infty}^{+\infty} e^{-2 \pi i s t} g(t) dt \cdot \int_{-\infty}^{+\infty} e^{-2 \pi i s t} f(t) dt \\ & = \int_{-\infty}^{+\infty} e^{-2 \pi i s t} g(t) dt \cdot \int_{-\infty}^{+\infty} e^{-2 \pi i s x} f(x) dx \\ & = \int_{-\infty}^{+\infty} \int_{-\infty}^{+\infty} e^{-2 \pi i s t} \cdot e^{-2 \pi i s x} \cdot g(t) \cdot f(x) dt dx \\ & = \int_{-\infty}^{+\infty} \int_{-\infty}^{+\infty} e^{-2 \pi i s (t + x)} \cdot g(t) \cdot f(x) dt dx \\ & = \int_{-\infty}^{+\infty} ( \int_{-\infty}^{+\infty} e^{-2 \pi i s (t + x)} \cdot g(t) dt ) f(x) dx\end{split}\\\begin{split}\\\end{split}\\Let: u = t + x \implies t = u - x\\\begin{split}\\\end{split}\\\begin{split}\mathcal{F} g(s) \cdot \mathcal{F} f(s) & = \int_{-\infty}^{+\infty} ( \int_{-\infty}^{+\infty} e^{-2 \pi i s (t + x)} \cdot g(t) dt ) f(x) dx \\ & = \int_{-\infty}^{+\infty} ( \int_{-\infty}^{+\infty} e^{-2 \pi i s u} \cdot g(u - x) du ) f(x) dx \\ & = \int_{-\infty}^{+\infty} e^{-2 \pi i s u} ( \int_{-\infty}^{+\infty} g(u - x) \cdot f(x) dx ) du\end{split}\\\begin{split}\\\end{split}\\Let: (f * g)(u) = \int_{-\infty}^{+\infty} g(u - x) \cdot f(x) dx\\\begin{split}\\\end{split}\\\begin{split}\mathcal{F} g(s) \cdot \mathcal{F} f(s) & = \int_{-\infty}^{+\infty} e^{-2 \pi i s u} ( \int_{-\infty}^{+\infty} g(u - x) \cdot f(x) dx ) du \\ & = \mathcal{F}(f * g)(s)\end{split}\end{aligned}\end{align} \]

similarly:

\[\mathcal{F}^{-1} F \cdot \mathcal{F}^{-1} G = \mathcal{F}^{-1} (F * G)\]

To prove the second statement we start with the first statement of the inverse Fourier transform:

\[ \begin{align}\begin{aligned}\mathcal{F}^{-1} F \cdot \mathcal{F}^{-1} G = \mathcal{F}^{-1} (F * G)\\\begin{split}\\\end{split}\\\therefore f \cdot g = \mathcal{F}^{-1} \left( \mathcal{F} f * \mathcal{F} g \right)\\\begin{split}\\\end{split}\\\therefore \mathcal{F} \left( f \cdot g \right) = \mathcal{F} f * \mathcal{F} g\end{aligned}\end{align} \]

Similarly:

\[\mathcal{F}^{-1} (F \cdot G) = \mathcal{F}^{-1} F * \mathcal{F}^{-1} G\]
\[\tag*{$\blacksquare$}\]

Back to Fourier Transform.