Published July 8, 2015 | Version Submitted + Published
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On the Uniqueness of Sparse Time-Frequency Representation of Multiscale Data

Abstract

In this paper, we analyze the uniqueness of the sparse time-frequency decomposition and investigate the efficiency of the nonlinear matching pursuit method. Under the assumption of scale separation, we show that the sparse time-frequency decomposition is unique up to an error that is determined by the scale separation property of the signal. We further show that the unique decomposition can be obtained approximately by the sparse time-frequency decomposition using nonlinear matching pursuit.

Additional Information

© 2015 SIAM. Received by the editors December 30, 2014; accepted for publication (in revised form) May 6, 2015; published electronically July 8, 2015. This work was supported by NSF FRG grants DMS-1159138 and DMS-1318377, AFOSR MURI grant FA9550-09-1-0613, and DOE grant DE-FG02-06ER25727.

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Published - 141002098.pdf

Submitted - 1501.04707v2.pdf

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Additional details

Identifiers

Eprint ID
61483
Resolver ID
CaltechAUTHORS:20151023-103928257

Related works

Funding

NSF
DMS-1159138
NSF
DMS-1318377
Air Force Office of Scientific Research (AFOSR)
FA9550-09-1-0613
Department of Energy (DOE)
DE-FG02-06ER25727

Dates

Created
2015-10-26
Created from EPrint's datestamp field
Updated
2021-11-10
Created from EPrint's last_modified field