There is growing evidence that nonlinear time series analysis techniques can be used to
successfully characterize, classify, or process signals derived from real-world dynamics
even though these are not necessarily deterministic and stationary. In the present study, we
proceed in this direction by addressing an important problem our modern society is facing,
the automatic classification of digital information. In particular, we address the automatic
identification of cover songs, ie alternative renditions of a previously recorded musical piece …