Fourier Transform Table – Definition and Applications

Fourier Transform Table Definition and Applications

This article explores the Fourier Transform table in-depth, illuminating its elements and providing insights into its numerous uses in the modern digital era.

Defining Fourier Transform Table

The Fourier Transform table is a table that lists common functions \( f(t) \) alongside their respective Fourier transforms \( F(\omega) \). The frequency domain representations (Fourier Transforms) of various time domain functions are provided by the Fourier Transform table, which is a collection of formulas.

This table is incredibly useful in technical fields, for instance, signal processing, control systems, and communication systems where we can use it to transform between the time and frequency domains.

If \( f(t) \) is a time-domain function, its Fourier Transform, often denoted as \( F(\omega) \) or \( F(f) \), is given by the integral:

\[ F(\omega) = \int_{-\infty}^{+\infty} f(t) e^{-j\omega t} \, dt \]

– \( f(t) \) is the function in the time domain.
– \( \omega \) is the angular frequency.
– \( j \) is the imaginary unit (square root of -1).


Signal Processing

In processing signals, whether audio, video, or any digital signal, Fourier Transforms help identify the frequency components of the signal. For tasks like noise filtering or amplifying particular frequency components, this is essential.

Communication Systems

It’s critical to comprehend the frequency components of signals in wireless communications. This ensures that signals are transmitted without interference and are received clearly.

Quantum Mechanics

The Fourier Transform is used to switch between the position and momentum representations of a quantum state.


In the study of light waves, the Fourier Transform aids in understanding diffraction patterns and the propagation of light through various media.


Magnetic Resonance Imaging (MRI) uses the Fourier Transform to convert the signals received from the body’s response to magnetic fields into images that depict different tissues’ structures.

CT Scans

Computed Tomography also utilizes Fourier techniques to reconstruct images from measured data.


Sound waves can be analyzed using Fourier Transforms to discern their constituent frequencies. This has applications in noise reduction, music production, and even architectural design to ensure optimal sound quality or noise insulation.

Geophysics and Seismology

Fourier Transforms help analyze the seismic waves generated during earthquakes. This analysis aids in understanding the earthquake’s source characteristics and the Earth’s subsurface structure.


For instance, Fourier Transform Nuclear Magnetic Resonance (FT-NMR) Spectroscopy, Fourier Transform Infrared (FTIR) Spectroscopy, Fourier Transform Raman Spectroscopy.

Fourier Transform Nuclear Magnetic Resonance (FT-NMR) Spectroscopy

  • Principle:

    • When nuclei are exposed to a magnetic field, they resonate at specific frequencies. By analyzing these resonances, chemists can infer details about the molecular structure of a compound.
    • Traditional NMR would sweep through frequencies, measuring one frequency at a time. This was time-consuming. FT-NMR, on the other hand, applies a wide range of frequencies simultaneously and measures the resulting free induction decay (FID) in the time domain.
    • This FID is then converted into a frequency domain spectrum using the Fourier Transform.
  • Applications:

    • Molecular Structure Determination: FT-NMR can provide insights into the arrangement of atoms within a molecule. The location and intensity of peaks in an NMR spectrum relate to the type and environment of the resonating nuclei, respectively.

    • Conformational Analysis: For molecules with flexible structures, FT-NMR can offer information about the different conformations that a molecule can adopt.

    • Dynamic Studies: It allows chemists to study processes like exchange reactions, tautomerism, and more.

Economics and Finance

Time series data, like stock prices, can be analyzed in the frequency domain to discern underlying patterns and cyclic behaviors not immediately apparent in the time domain.

Mathematics and Mathematical Physics

The Fourier Transform table simplifies the solution process for many differential equations, integral equations, and other mathematical problems by transforming them into an easier domain.

Astronomy and Astrophysics

It is possible to determine the frequencies that celestial bodies are generating by modifying signals from space in radio astronomy, which aids in our understanding of their characteristics and behaviors.


Example 1

Delta Function

Time-domain function: (Delta function)

Fourier Transform:

\[ F\{\delta(t)\} = \int_{-\infty}^{\infty} \delta(t) e^{-j\omega t} \, dt\]


Given the properties of the delta function, the integral evaluates to 1 at . Hence, the Fourier Transform is:

\[F\{\delta(t)\} = 1\]

Example 2

Rectangular Pulse

Time-domain function: This function is 1 from −1/2 to 1/2 and 0 otherwise.

Fourier Transform:

\[F\{rect(t)\} = \int_{-\infty}^{\infty} rect(t) e^{-j\omega t} , dt\]


The integral evaluates to:

\[F\{rect(t)\} = \int_{-\frac{1}{2}}^{\frac{1}{2}} e^{-j\omega t} , dt = \frac{\omega}{2} \sin\left(\frac{\omega}{2}\right) = \text{sinc}\left(\frac{\omega}{2}\right)\]

Example 3

Exponential function

Time-domain function:

\[ x(t) = e^{-at} u(t) \]

where and is the unit step function.

Fourier Transform:

\[ F\{e^{-at} u(t)\} = \int_{-\infty}^{\infty} e^{-at} u(t) e^{-j\omega t} \, dt \]


Considering the unit step function, we only need to evaluate the integral from 0 to infinity: