Literature DB >> 28197956

Sufficient conditions for uniqueness in Candecomp/Parafac and Indscal with random component matrices.

Alwin Stegeman1,2, Jos M F Ten Berge3, Lieven De Lathauwer4.   

Abstract

A key feature of the analysis of three-way arrays by Candecomp/Parafac is the essential uniqueness of the trilinear decomposition. We examine the uniqueness of the Candecomp/Parafac and Indscal decompositions. In the latter, the array to be decomposed has symmetric slices. We consider the case where two component matrices are randomly sampled from a continuous distribution, and the third component matrix has full column rank. In this context, we obtain almost sure sufficient uniqueness conditions for the Candecomp/Parafac and Indscal models separately, involving only the order of the three-way array and the number of components in the decomposition. Both uniqueness conditions are closer to necessity than the classical uniqueness condition by Kruskal.

Keywords:  Candecomp; Indscal; Parafac; three-way arrays; uniqueness

Year:  2017        PMID: 28197956     DOI: 10.1007/11336-006-1278-2

Source DB:  PubMed          Journal:  Psychometrika        ISSN: 0033-3123            Impact factor:   2.500


  3 in total

1.  Resolving complex mixtures: trilinear diffusion data.

Authors:  Johannes Björnerås; Adolfo Botana; Gareth A Morris; Mathias Nilsson
Journal:  J Biomol NMR       Date:  2013-06-28       Impact factor: 2.835

2.  Constrained Candecomp/Parafac via the Lasso.

Authors:  Paolo Giordani; Roberto Rocci
Journal:  Psychometrika       Date:  2013-02-07       Impact factor: 2.500

3.  Factor Uniqueness of the Structural Parafac Model.

Authors:  Paolo Giordani; Roberto Rocci; Giuseppe Bove
Journal:  Psychometrika       Date:  2020-08-16       Impact factor: 2.500

  3 in total

北京卡尤迪生物科技股份有限公司 © 2022-2023.