Skip to main content

Frequency, Quefrency, and Phase in Practice

  • Chapter
  • 3782 Accesses

Part of the book series: Use R! ((USE R))

Abstract

The options to compute, display, and describe the frequency spectrum are reviewed. This includes the use of different frequency and amplitude scales, the automatic detection of frequency peaks in particular the fundamental frequency peak and the dominant frequency peak, the identification of harmonics series, the principle of symbolic aggregate approximation, and the use of other spectrum parametrizations. The quefrency cepstrum and the phase portrait are also introduced.

Audio files:Loxodonta_africana.wavtico.wavpeewit.wavsheep.wavorni.wavpellucens.wav

This is a preview of subscription content, log in via an institution.

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   64.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   84.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Notes

  1. 1.

    A derived version of specprop() is available in the package warbleR under the name specan().

References

  • Adler D, Murdoch D (2016) rgl: 3D visualization device system (OpenGL). http://CRAN.R-project.org/package=rgl, R package

  • Aldersley A, Champneys A, Homer M, Robert D (2016) Quantitative analysis of harmonic convergence in mosquito auditory interactions. J R Soc Interface 13:20151007

    Google Scholar 

  • Bennet-Clark HC (1999) Which Qs to choose: questions of quality in bioacoustics? Bioacoustics 9:351–359

    Google Scholar 

  • Bradbury JW, Vehrencamp SL (1998) Principles of animal communication. Sinauer Associates, Sunderland

    Google Scholar 

  • Carson JR (1922) Notes on the theory of modulation. Proc Institute Radio Eng 10:57–64

    Google Scholar 

  • Cazelles B (2004) Symbolic dynamics for identifying similarity between rhythms of ecological time series. Ecol Lett 7:755–763

    Google Scholar 

  • Chowning JM (1973) The synthesis of complex audio spectra by means of frequency modulation. J Audio Eng Soc 21:526–531

    Google Scholar 

  • Fitch W, Neubauer J, Herzel H (2002) Calls out of chaos: the adaptive significance of nonlinear phenomena in mammalian vocal production. Anim Behav 63:407–418

    Google Scholar 

  • Gilbert J, Dalmont JP, Potier R, Reby D (2014) Is nonlinear propagation responsible for the brassiness of elephant trumpet calls? Acta Acustica United Acustica 100:734–738

    Google Scholar 

  • Kantz H, Schreiber T (2003) Non linear time series analysis. Cambridge University Press, Cambridge

    Google Scholar 

  • Kasten EP, Gage SH, Fox J, Joo W (2012) The remote environmental assessment laboratory’s acoustic library: an archive for studying soundscape ecology. Eco Inform 12:50–67

    Google Scholar 

  • Lauterborn W, Parlitz U (1988) Methods of chaos physics and their application to acoustics. J Acoust Soc Am 84:1975–1993

    Google Scholar 

  • Lin J, Keogh E, Lonardi S, Chiu B (2003) A symbolic representation of time series, with implications for streaming algorithms. In: Proceedings of the 8th ACM SIGMOD workshop on research issues in data mining and knowledge discovery, DMKD ’03. ACM, New York, pp 2–11

    Google Scholar 

  • Mezquida DA, Martinez JL (2009) Platform for beehives monitoring based on sound analysis. a perpetual warehouse for swarm’s daily activity. Span J Agric Res 7:824–828

    Google Scholar 

  • Ramsay JO, Silverman BW (2005) Functional data analysis. Springer, New York

    Google Scholar 

  • Rice AN, Land BR, Bass AH (2011) Nonlinear acoustic complexity in a fish “two-voice” system. Proc R Soc B: Biol Sci 278:3762–3768

    Google Scholar 

  • Senin P (2015) jmotif: tools for time series analysis based on symbolic aggregate discretization. http://CRAN.R-project.org/package=jmotif, R package

  • Tokuda IT (2017) Nonlinear dynamics and temporal analysis. In: Comparative bioacoustics: an overview. Bentham Science, Oak Park, pp 336–357

    Google Scholar 

  • Wickham H (2009) ggplot2. Elegant graphics for data analysis. Springer, Dordrecht

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

Copyright information

© 2018 Springer International Publishing AG, part of Springer Nature

About this chapter

Cite this chapter

Sueur, J. (2018). Frequency, Quefrency, and Phase in Practice. In: Sound Analysis and Synthesis with R. Use R!. Springer, Cham. https://doi.org/10.1007/978-3-319-77647-7_10

Download citation

Publish with us

Policies and ethics