A Hypothesis Testing Approach to Nonstationary Source Separation

• URL: http://arxiv.org/abs/2105.06958v1
• Date: Fri, 14 May 2021 16:58:55 GMT
• Title: A Hypothesis Testing Approach to Nonstationary Source Separation
• Authors: Reza Sameni, Christian Jutten
• Abstract summary: The extraction of nonstationary signals from blind and semi-blind multivariate observations is a recurrent problem. Various methods for nonstationarity identification are reviewed and a new general framework based on hypothesis testing is proposed. The proposed method is applied to noninvasive fetal ECG extraction, as case study.
• Score: 15.193722258844517
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: The extraction of nonstationary signals from blind and semi-blind multivariate observations is a recurrent problem. Numerous algorithms have been developed for this problem, which are based on the exact or approximate joint diagonalization of second or higher order cumulant matrices/tensors of multichannel data. While a great body of research has been dedicated to joint diagonalization algorithms, the selection of the diagonalized matrix/tensor set remains highly problem-specific. Herein, various methods for nonstationarity identification are reviewed and a new general framework based on hypothesis testing is proposed, which results in a classification/clustering perspective to semi-blind source separation of nonstationary components. The proposed method is applied to noninvasive fetal ECG extraction, as case study.

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