Automatic extraction of time-frequency skeletons with minimal spanning trees

Author

Michel, Olivier ; Flandrin, Patrick ; Hero, Alfred O., II

Author_Institution

Lab. de Phys., Ecole Normale Superieure de Lyon, France

Volume

1

fYear

2000

fDate

2000

Firstpage

89

Abstract

Theoretical results have been established in non-parametric entropy estimation, based on asymptotic properties of minimal spanning trees (MST). A new application is proposed for the automatic extraction of time-frequency skeletons in the case of multicomponent chirp-like signals. The proposed method makes use of local maxima of a time-frequency distribution (considered as realizations of a 2D or 3D process), and exploits the efficiency of MSTs for density discrimination and clustering

Keywords

entropy; feature extraction; pattern clustering; spectral analysis; time-frequency analysis; trees (mathematics); 2D process; 3D process; asymptotic properties; automatic extraction; clustering; density discrimination; information theory; local maxima; minimal spanning trees; multicomponent chirp-like signals; nonparametric entropy estimation; spectrograms; time-frequency distribution; time-frequency skeletons; Chirp; Computational efficiency; Entropy; Integrated circuit noise; Joining processes; Robustness; Signal processing; Skeleton; Time frequency analysis; Tree graphs;

fLanguage

English

Publisher

ieee

Conference_Titel

Acoustics, Speech, and Signal Processing, 2000. ICASSP '00. Proceedings. 2000 IEEE International Conference on

Conference_Location

Istanbul

ISSN

1520-6149

Print_ISBN

0-7803-6293-4

Type

conf

DOI

10.1109/ICASSP.2000.861871

Filename

861871