JSM 2005 Online Program

Abstract #302348

This is the preliminary program for the 2005 Joint Statistical Meetings in Minneapolis, Minnesota. Currently included in this program is the "technical" program, schedule of invited, topic contributed, regular contributed and poster sessions; Continuing Education courses (August 7-10, 2005); and Committee and Business Meetings. This on-line program will be updated frequently to reflect the most current revisions.

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Activity Number:	434
Type:	Invited
Date/Time:	Wednesday, August 10, 2005 : 2:00 PM to 3:50 PM
Sponsor:	Section on Nonparametric Statistics
Abstract - #302348
Title:	Chirplets: Multiscale Detection and Recovery of Chirps from Very Noisy Data
Author(s):	Emmanuel J. Candes*+
Companies:	California Institute of Technology
Address:	Mail Code 217-50, Pasadena, CA, 91125, USA
Keywords:	Nonparametric detection ; time-frequency analysis ; gravitational waves ; chirps ; shortest paths
Abstract:	In this talk, we consider the problem of detecting and recovering chirps from noisy data. Chirps are signals that are neither smoothly varying nor stationary. Rather, they exhibit rapid oscillations and changes in their frequency content. This behavior is different from that assumed in the standard literature, which typically assumes smoothness and homogeneity. One particular application of note in conjunction with this line of research is the detection of gravitational waves. Building on recent advances in computational harmonic analysis, we design libraries of multiscale chirplets and introduce detection strategies that are more sensitive than existing feature detectors. The idea is to use structured algorithms that exploit information in the chirplet dictionary to chain chirplets together adaptively as to form chirps with polygonal instantaneous frequency; these structured algorithms are so sensitive they allow to detect signals whenever their strength makes them detectable by any method, no matter how intractable.

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