Stationarity stopping criterion for matching pursuit—framework and encephalographic illustration
We present a new stopping criterion for the matching pursuit (MP) algorithm, based on evaluating stationarity of the residua of the consecutive MP iterations. The new stopping criterion is based on a model of a nonstationary signal, which assumes that the part of the signal that is of interest is no...
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| Veröffentlicht in: | Biological cybernetics 2011-12, Vol.105 (5-6), p.287-290 |
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| container_title | Biological cybernetics |
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| creator | Kipiski, Lech |
| description | We present a new stopping criterion for the matching pursuit (MP) algorithm, based on evaluating stationarity of the residua of the consecutive MP iterations. The new stopping criterion is based on a model of a nonstationary signal, which assumes that the part of the signal that is of interest is nonstationary and contaminated by a weakly stationary noise. Mean- and variance-stationarity of the residua obtained from each step of MP is evaluated by means of dedicated statistical tests—the Kwiatkowski–Phillips–Schmidt–Shin (KPSS) test and the White test, respectively. We illustrate the proposed concept by an example in which we analyse magnetoencephalographic (MEG) data. |
| doi_str_mv | 10.1007/s00422-011-0443-9 |
| format | Article |
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| subjects | Algorithms Bioinformatics Biomedical and Life Sciences Biomedicine Brain - physiology Brain Waves - physiology Complex Systems Computer Appl. in Life Sciences Contamination Criteria Cybernetics Electroencephalography Humans Illustrations Iterative methods Magnetoencephalography Matching Models, Neurological Neurobiology Neurosciences Noise Original Paper Signal Processing, Computer-Assisted |
| title | Stationarity stopping criterion for matching pursuit—framework and encephalographic illustration |
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