Fractional Fourier Transform (FRFT)

This tutorial was prepared by Behzad Haki and Esteban Gutiérrez

    1. Fractional Fourier Sound Synthesis

      Esteban Gutiérrez, Rodrigo Cádiz, Carlos Sing Long, and 2 more
       · 2025
      Abstract

      This paper explores the innovative application of the Fractional Fourier Transform (FrFT) in sound synthesis, highlighting its potential to redefine time-frequency analysis in audio processing. As an extension of the classical Fourier Transform, the FrFT introduces fractional order parameters, enabling a continuous interpolation between time and frequency domains and unlocking unprecedented flexibility in signal manipulation. Crucially, the FrFT also opens the possibility of directly synthesizing sounds in the alpha-domain, providing a unique framework for creating timbral and dynamic characteristics unattainable through conventional methods. This work delves into the mathematical principles of the FrFT, its historical evolution, and its capabilities for synthesizing complex audio textures. Through experimental analyses, we showcase novel sound design techniques, such as alpha-synthesis and alpha-filtering, which leverage the FrFT’s time-frequency rotation properties to produce innovative sonic results. The findings affirm the FrFT’s value as a transformative tool for composers, sound designers, and researchers seeking to push the boundaries of auditory creativity.

      BibTeX
      @misc{gutierrez2025fractionalfouriersoundsynthesis,
        title = {Fractional Fourier Sound Synthesis},
        author = {Guti{\'e}rrez, Esteban and C{\'a}diz, Rodrigo and Long, Carlos Sing and Font, Frederic and Serra, Xavier},
        year = {2025},
        eprint = {2506.09189},
        archiveprefix = {arXiv},
        primaryclass = {cs.SD},
      }

    MIT

    Tutorial

    What is Fractional Fourier Transform (FRFT)?

    FRFT relationship with FFT

    FRFT Properties

    Applying FRFT to Pure Tones

    Impact of Windowing

    Block-based Analysis

    FRFT for Synthesis and Processing

    Using FRFT in Real-Time