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Smooth Interpolation of Covariance Matrices and Brain Network Estimation
We propose an approach to use the state covariance of autonomous linear systems to track time-varying covariance matrices of nonstationary time series. Following concepts from the Riemannian geometry, we investigate three types of covariance paths obtained by using different quadratic regularization...
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| Publicado no: | IEEE Trans Automat Contr |
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| Autor principal: | |
| Formato: | Artigo |
| Idioma: | Inglês |
| Publicado em: |
2018
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| Assuntos: | |
| Acesso em linha: | https://ncbi.nlm.nih.gov/pmc/articles/PMC8074851/ https://ncbi.nlm.nih.gov/pubmed/33907337 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1109/tac.2018.2879597 |
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