Multilinear principal component analysis: Difference between revisions

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{{context|date=June 2012}}

'''Multilinear Principal Component Analysis''' (MPCA) is a multilinear extension of [[principal component analysis]] (PCA). MPCA is employed in the analysis of n-way arrays, ie a cube or hyper-cube of numbers, also informally knownreferred to as a "data tensor". N-way arrays may be decomposed, andanalyzed, or modeled by

* linear tensor models bysuch employingas aCANDECOMP/Parafac, rank-Ror tensor decomposition, or

* multilinear tensor models, such multilinear principal component analysis (MPCA), or multilinear independent component analysys (MICA)., etc

The origin of MPCA can be traced back to the [[Tucker decomposition]]<ref>{{Cite journal|last1=Tucker| first1=Ledyard R

| authorlink1 = Ledyard R Tucker