Decoding the Encoding of Functional Brain Networks: an fMRI Classification Comparison of Non-negative Matrix Factorization (NMF), Independent Component Analysis (ICA), and Sparse Coding Algorithms.
Jianwen XiePamela K. DouglasYing Nian WuArthur L. BrodyAriana E. AndersonPublished in: CoRR (2016)
Keyphrases
- negative matrix factorization
- independent component analysis
- principal component analysis
- sparse representation
- blind source separation
- nonnegative matrix factorization
- sparse coding
- dictionary learning
- sparsity constraints
- signal processing
- natural image statistics
- feature space
- image classification
- independent components
- feature extraction
- factor analysis
- matrix factorization
- face recognition
- principal components
- text classification
- unsupervised learning
- document clustering
- image representation
- pattern recognition
- supervised learning
- eeg data
- singular value decomposition
- human brain
- image patches
- learning algorithm
- linear combination
- least squares
- data analysis
- image processing