Determining the Properties of a Signal Based on its Fourier Transform
As part of this course, it is important to be able to examine the Fourier Transform of a signal, and tell if the original signal is real, pure imaginary, even, or odd. This article contains proof of properties that can help with this determination, and a few short example problems.
Table of Properties
| Real X(w) | Imaginary X(w) | |
| Even X(w) | Real and Even x(t) | Imaginary and Even x(t) |
| Odd X(w) | Imaginary and Odd x(t) | Real and Odd x(t) |
Proofs
The first proof, that the Fourier Transform of a real and even signal is also real and even, was completed by Prof. Boutin, as part of the class notes. I have put it here for convenience and make no attempt to claim it as my own. The remaining proofs are my own.
Real and Even Signals have Real and Even Fourier Transforms
Since x(t) is real:
$ x*(t) = x(t) $
$ \mathfrak{F}(x*(t)) = \mathfrak{F}(x(t)) $
$ \chi * ( - \omega ) = \chi ( \omega ) $ , by conjugation property of CTFT
$ \Re ( \chi (- \omega )) - \jmath \Im ( \chi (- \omega )) = \Re ( \chi (- \omega )) + \jmath \Im ( \chi ( \omega )) $ Therefore, this splits into the even, real equation: $ \Re ( \chi (- \omega )) = \Re ( \chi (- \omega )) $ And the odd, imaginary equation: $ - \Im ( \chi (- \omega )) = \Im ( \chi ( \omega )) $
This means that when x(t) is real, the real part of $ \chi ( \omega ) $ will be even, and the imaginary part will be odd. If, also x(t) is even:
$ x(-t) = x(t) $
$ \chi (- \omega ) = \int_{-\infty}^{\infty} x(t) e^{ \jmath (-\omega) t} dt $ $ \chi (- \omega ) = \int_{-\infty}^{\infty} x(-\tau) e^{ \jmath \omega \tau } dt $
