Mathematical Sciences

Lund University

  • Title: Classification of bird song syllables using low-rank approximations of time-frequency images
  • Short description:

    A bird's song is used as an identification tool, serving as a recognition signal to indicate the individual, the kinship and the species. The studies so far are however impaired by the lack of methods which would automatically and objectively analyse the song structure. In this project, the singular vectors when decomposing the multitaper spectrogram image are proposed to be used as feature vectors in classification of bird song syllables. The approach is expected to be especially suitable for signals consisting stochastic components with variance in amplitudes as well as time- and frequency locations.

    Prerequisites: FMSF10/MASC04, FMSN35/MASM26

  • Long description:

    None

  • Contact: Maria Sandsten