An analysis of the persistence of Zonotrichia capensis themes using dynamical systems and machine learning tools
Roberto Bistel,
Alejandro Martinez and
Gabriel B. Mindlin
Chaos, Solitons & Fractals, 2022, vol. 165, issue P1
Abstract:
In this work, we use tools from nonlinear dynamics to generate synthetic bird songs with frequency modulations compatible with sketches reported in a study of chingolo (Zonotrichia capensis) songs in 1966. Using machine learning tools, we conclude that some of the sketches correspond to themes that are still sang in the same region, five decades later.
Keywords: Birdsong; Neural networks; Models of phonation (search for similar items in EconPapers)
Date: 2022
References: View complete reference list from CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0960077922009821
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:chsofr:v:165:y:2022:i:p1:s0960077922009821
DOI: 10.1016/j.chaos.2022.112803
Access Statistics for this article
Chaos, Solitons & Fractals is currently edited by Stefano Boccaletti and Stelios Bekiros
More articles in Chaos, Solitons & Fractals from Elsevier
Bibliographic data for series maintained by Thayer, Thomas R. ().