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Published July 8, 2015 | Published + Submitted
Journal Article Open

On the Uniqueness of Sparse Time-Frequency Representation of Multiscale Data


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.

Attached Files

Published - 141002098.pdf

Submitted - 1501.04707v2.pdf


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August 20, 2023
August 20, 2023