In independent component analysis (ICA), principal component analysis (PCA) is generally used to reduce the raw data to a few principal components (PCs) through eigenvector decomposition (EVD) on the data covariance matrix. Although this works for spatial ICA (sICA) on moderately sized fMRI data, it
โฆ LIBER โฆ
Strategies for MCR image analysis of large hyperspectral data-sets
โ Scribed by David J. Scurr; Andrew L. Hook; Jonathan Burley; Philip M. Williams; Daniel G. Anderson; Robert Langer; Martyn C. Davies; Morgan R. Alexander
- Book ID
- 112206866
- Publisher
- John Wiley and Sons
- Year
- 2012
- Tongue
- English
- Weight
- 459 KB
- Volume
- 45
- Category
- Article
- ISSN
- 0142-2421
- DOI
- 10.1002/sia.5040
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