• DocumentCode
    1124959
  • Title

    Alias-Suppressed Oscillators Based on Differentiated Polynomial Waveforms

  • Author

    Välimäki, Vesa ; Nam, Juhan ; Smith, Julius O. ; Abel, Jonathan S.

  • Author_Institution
    Dept. of Signal Process. & Acoust., TKK-Helsinki Univ. of Technol., Espoo, Finland
  • Volume
    18
  • Issue
    4
  • fYear
    2010
  • fDate
    5/1/2010 12:00:00 AM
  • Firstpage
    786
  • Lastpage
    798
  • Abstract
    An efficient approach to the generation of classical synthesizer waveforms with reduced aliasing is proposed. This paper introduces two new classes of polynomial waveforms that can be differentiated one or more times to obtain an improved version of the sampled sawtooth and triangular signals. The differentiated polynomial waveforms (DPW) extend the previous differentiated parabolic wave method to higher polynomial orders, providing improved alias-suppression. Suitable polynomials of order higher than two can be derived either by analytically integrating a previous lower order polynomial or by solving the polynomial coefficients directly from a set of equations based on constraints. We also show how rectangular waveforms can be easily produced by differentiating a triangular signal. Bandlimited impulse trains can be obtained by differentiating the sawtooth or the rectangular signal. An objective evaluation using masking and hearing threshold models shows that a fourth-order DPW method is perceptually alias-free over the whole register of the grand piano. The proposed methods are applicable in digital implementations of subtractive sound synthesis.
  • Keywords
    acoustic signal processing; audio-frequency oscillators; signal synthesis; acoustic signal processing; alias-suppressed oscillators; audio oscillators; classical synthesizer waveforms; differentiated polynomial waveforms; reduced aliasing; signal synthesis; Acoustic signal processing; antialiasing; audio oscillators; music; signal synthesis;
  • fLanguage
    English
  • Journal_Title
    Audio, Speech, and Language Processing, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    1558-7916
  • Type

    jour

  • DOI
    10.1109/TASL.2009.2026507
  • Filename
    5153306