Some wavelet analyses of point process data

Author

Brillinger, David R.

Author_Institution

Dept. of Stat., California Univ., Berkeley, CA, USA

Volume

2

fYear

1997

fDate

2-5 Nov. 1997

Firstpage

1087

Abstract

Point processes may be described by conditional intensity functions and moments. Wavelet analysis provides a means of parameterizing such quantities in the nonstationary case. The parameters of the wavelet expansion may themselves be estimated by the method of moments or likelihood analysis. These ideas are illustrated for data sets arising from nerve cells firing and earthquakes occurring. In particular wavelet parameterized rate, autointensity and conditional intensity functions are estimated.

Keywords

bioelectric phenomena; earthquakes; geophysical signal processing; medical signal processing; method of moments; neurophysiology; signal processing; stochastic processes; wavelet transforms; autointensity; conditional intensity functions; data sets; earthquakes occurrence; firing nerve cells; likelihood analysis; method of moments; nonstationary case; point process data; wavelet analyses; wavelet expansion; wavelet parameterized rate; Damping; Earthquakes; History; Image analysis; Random processes; Smoothing methods; Statistics; Time series analysis; Wavelet analysis;

fLanguage

English

Publisher

ieee

Conference_Titel

Signals, Systems & Computers, 1997. Conference Record of the Thirty-First Asilomar Conference on

Conference_Location

Pacific Grove, CA, USA

ISSN

1058-6393

Print_ISBN

0-8186-8316-3

Type

conf

DOI

10.1109/ACSSC.1997.679073

Filename

679073