Title
Sparse coding with anomaly detection
Abstract
We consider the problem of simultaneous sparse coding and anomaly detection in a collection of data vectors. The majority of the data vectors are assumed to conform with a sparse representation model, whereas the anomaly is caused by an unknown subset of the data vectors - the outliers - which significantly deviate from this model. The proposed approach utilizes the Alternating Direction Method of Multipliers (ADMM) to recover simultaneously the sparse representations and the outliers components for the entire collection. This approach provides a unified solution both for jointly sparse and independently sparse data vectors. We demonstrate the usefulness of the proposed approach for irregular heartbeats detection in Electrocardiogram (ECG) and specular reflectance removal from natural images.
Year
DOI
Venue
2013
10.1007/s11265-014-0913-0
Journal of Signal Processing Systems
Keywords
DocType
Volume
Sparse coding,Anomaly detection,ADMM,Arrythmia detection,Specular reflectance removal,Shadows removal
Conference
79
Issue
ISSN
Citations 
2
1939-8018
27
PageRank 
References 
Authors
0.89
17
4
Name
Order
Citations
PageRank
Amir Adler1968.81
Michael Elad211274854.93
Yacov Hel-Or346140.74
Ehud Rivlin460840.67