An operator-based and sparsity-based approach to adaptive signal separation

An operator-based and sparsity-based approach is proposed to adaptively separate a signal into additive subcomponents. The proposed approach can be formulated as an optimization problem. Since the design of the operator can be adaptively customized to the target signal, we can propose different type...

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Bibliographic Details
Published in2013 IEEE International Conference on Acoustics, Speech and Signal Processing pp. 6186 - 6190
Main Authors Xiaolei Yi, Xiyuan Hu, Silong Peng
Format Conference Proceeding
LanguageEnglish
Published IEEE 01.05.2013
Subjects
adaptive operator
Additives
Electrocardiography
Equations
Null space
Optimization
Signal separation
Source separation
Sparse matrices
sparse signal
the null space
ℓ 1 constraint
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Summary:An operator-based and sparsity-based approach is proposed to adaptively separate a signal into additive subcomponents. The proposed approach can be formulated as an optimization problem. Since the design of the operator can be adaptively customized to the target signal, we can propose different types of operators for different types of signals. The subcomponents are a kind of local narrow band signals in the null space of an adaptive operator and a residual signal which is a sparse signal in some sense. Our experiments, including simulated signals and a real-life signal, demonstrate the efficacy and accuracy of the proposed approach.
ISSN:1520-6149
2379-190X
DOI:10.1109/ICASSP.2013.6638854