Signal segmentation and denoising algorithm based on energy optimisation
Signal segmentation and denoising algorithm based on energy optimisation
A nonlinear functional is considered in this short communication for time interval segmentation and noise reduction of signals. An efficient algorithm that exploits the signal geometrical properties is proposed to optimise the nonlinear functional for signal smoothing. Discontinuities separating consecutive time intervals of the original signal are initially detected by measuring the curvature and arc length of the smoothed signal. The nonlinear functional is then optimised for each time interval to achieve noise reduction of the original noisy signal. This algorithm exhibits robustness for signals characterised by very low signal to noise ratios.
Nonlinear energy optimisation, Signal segmentation, Signal smoothing
1845-1851
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Sharif, Bayan
d57a4cae-a6f0-4ab3-b2d8-ef594a75857f
10 December 2005
Mahmoodi, Sasan
91ca8da4-95dc-4c1e-ac0e-f2c08d6ac7cf
Sharif, Bayan
d57a4cae-a6f0-4ab3-b2d8-ef594a75857f
Mahmoodi, Sasan and Sharif, Bayan
(2005)
Signal segmentation and denoising algorithm based on energy optimisation.
Signal Processing, 85 (9), .
Abstract
A nonlinear functional is considered in this short communication for time interval segmentation and noise reduction of signals. An efficient algorithm that exploits the signal geometrical properties is proposed to optimise the nonlinear functional for signal smoothing. Discontinuities separating consecutive time intervals of the original signal are initially detected by measuring the curvature and arc length of the smoothed signal. The nonlinear functional is then optimised for each time interval to achieve noise reduction of the original noisy signal. This algorithm exhibits robustness for signals characterised by very low signal to noise ratios.
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SignalProcessing2005.pdf
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Published date: 10 December 2005
Keywords:
Nonlinear energy optimisation, Signal segmentation, Signal smoothing
Organisations:
Southampton Wireless Group
Identifiers
Local EPrints ID: 265860
URI: http://eprints.soton.ac.uk/id/eprint/265860
ISSN: 0165-1684
PURE UUID: bacf08b8-c4ab-4d90-8964-812a4638f1ad
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Date deposited: 09 Jun 2008 12:17
Last modified: 14 Mar 2024 08:16
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Contributors
Author:
Sasan Mahmoodi
Author:
Bayan Sharif
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