Hybrid linear/quadratic time-frequency attributes

Author

Baraniuk, Richard G. ; Coates, Mark ; Steeghs, Philippe

Author_Institution

Dept. of Electr. & Comput. Eng., Rice Univ., Houston, TX, USA

Volume

49

Issue

4

fYear

2001

fDate

4/1/2001 12:00:00 AM

Firstpage

760

Lastpage

766

Abstract

We present an efficient method for robustly calculating time-frequency attributes of a signal, including instantaneous mean frequency, bandwidth, kurtosis, and other moments. Most current attribute estimation techniques involve a costly intermediate step of computing a (highly oversampled) two-dimensonal (2-D) quadratic time-frequency representation (TFR), which is then collapsed to the one-dimensonal (1-D) attribute. Using the principles of hybrid linear/quadratic time-frequency analysis (time-frequency distribution series), we propose computing attributes as nonlinear combinations of the (slightly oversampled) linear Gabor coefficients of the signal. The method is both computationally efficient and accurate; it performs as well as the best techniques based on adaptive TFRs. To illustrate, we calculate an attribute of a seismic cross section

Keywords

estimation theory; geophysical signal processing; seismology; signal representation; time-frequency analysis; transforms; attribute estimation techniques; bandwidth; hybrid linear/quadratic time-frequency attributes; instantaneous mean frequency; kurtosis; linear Gabor coefficients; moments; nonlinear combinations; seismic cross section; time-frequency distribution series; Bandwidth; Distributed computing; Frequency estimation; Neurophysiology; Phase estimation; Robustness; Signal analysis; Signal generators; Time series analysis; Two dimensional displays;

fLanguage

English

Journal_Title

Signal Processing, IEEE Transactions on

Publisher

ieee

ISSN

1053-587X

Type

jour

DOI

10.1109/78.912920

Filename

912920