Convolutional Sparse Coding for Time Series Via a ℓ0 Penalty: An Efficient Algorithm With Statistical Guarantees

ABSTRACT Identifying characteristic patterns in time series, such as heartbeats or brain responses to a stimulus, is critical to understanding the physical or physiological phenomena monitored with sensors. Convolutional sparse coding (CSC) methods, which aim to approximate signals by a sparse combi...

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Bibliographic Details
Published in:	Statistical analysis and data mining Vol. 17; no. 6
Main Authors:	Truong, Charles, Moreau, Thomas
Format:	Journal Article
Language:	English
Published:	Hoboken Wiley Subscription Services, Inc., A Wiley Company 01.12.2024 Wiley Subscription Services, Inc Wiley
Subjects:	Algorithms Atomic properties Coding compressive statistical learning Computer Science convolutional sparse coding Error analysis Error correction Error detection L0 penalty Mathematics Noise measurement Optimization Physiology signal processing Statistics Time series convolutional sparse coding statistical learning L0 penalty compressive statistical learning signal processing
ISSN:	1932-1864, 1932-1872
Online Access:	Get full text
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