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Sample-Poor Estimation of Order and Common Signal Subspace with Application to Fusion of Medical Imaging Data
Due to their data-driven nature, multivariate methods such as canonical correlation analysis (CCA) have proven very useful for fusion of multimodal neurological data. However, being able to determine the degree of similarity between datasets and appropriate order selection are crucial to the success...
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| Publicat a: | Neuroimage |
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| Autors principals: | , , , , |
| Format: | Artigo |
| Idioma: | Inglês |
| Publicat: |
2016
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| Matèries: | |
| Accés en línia: | https://ncbi.nlm.nih.gov/pmc/articles/PMC4912912/ https://ncbi.nlm.nih.gov/pubmed/27039696 https://ncbi.nlm.nih.govhttp://dx.doi.org/10.1016/j.neuroimage.2016.03.058 |
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