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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...

Deskribapen osoa

Gorde:
Xehetasun bibliografikoak
Argitaratua izan da:Neuroimage
Egile Nagusiak: Levin-Schwartz, Yuri, Song, Yang, Schreier, Peter J., Calhoun, Vince D., Adalı, Tülay
Formatua: Artigo
Hizkuntza:Inglês
Argitaratua: 2016
Gaiak:
Sarrera elektronikoa: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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