Non-rotational Tucker3 core simplification

A simple and efficient approach is reported to estimate the sparsest Tucker3 model for a considered linear dependent multiway data array using PARAFAC profiles. Employing the least possible number of non -zero core elements equal to the pseudo array rank of data, a better and easier interpretation of the data array is possible. The approach does not require any prior information. The type of rank deficiency, that is rank overlap or closure in different modes, and the Tucker3 core size can be determined from a congruency factor while running the algorithm. The replacement method (RM) of optimization is applied to determine the pattern (positions and values) of non -zero elements in the sparsest core of the Tucker3 model. Full rank and rank deficient simulated data sets in different conditions as well as an experimental 3D fluorescence data set from gold nanoparticle (AuNP) interaction with HIV genome are successfully used for evaluating the performance of the algorithm. Copyright (C) 2016 John Wiley & Sons, Ltd.