Transient Artifact Reduction Algorithm (TARA) based on Sparse Optimization
IEEE Transactions on Signal Processing, 2014.
Ivan W. Selesnick, Harry L. Graber, Yin Ding, Tong Zhang, Randall L. Barbour
Web:
http://eeweb.poly.edu/iselesni/tara/
Software version: 1
This software accompanies the above paper which addresses the suppression of transient artifacts in signals,
e.g., biomedical time series.
Matlab implementation of transient artifact reduction algorithm (TARA)
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lpfcsd.m: low-pass filtering / compound sparse denoising
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lpfcsd2.m: LPFCSD with input parameters {theta, sigma}
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tara_L1.m: TARA using the L1 norm penalty
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tara2_L1.m: TARA using the L1 norm penalty, with input parameters {theta, beta, sigma}
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tara.m: TARA with non-convex penalties
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tara2.m: TARA with non-convex penalties, with input parameters {theta, beta, sigma}
Examples in Matlab
Acknowledgment
This research was supported by the NSF under Grant No. CCF-1018020,
the NIH under Grant Nos. R42NS050007, R44NS049734, and R21NS067278, and by DARPA project N66001-10-C-2008.