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Bibliografie

Conference Paper (international conference)

On Revealing Replicating Structures in Multiway Data: A Novel Tensor Decomposition Approach

Phan A. H., Cichocki A., Tichavský Petr, Mandic D., Matsuoka K.

: Latent Variable Analysis and Signal Separation, p. 297-305 , Eds: Theis Fabian

: Latent Variable Analysis and Signal Separation,10th International Conference, LVA/ICA 2012, (Tel Aviv, IL, 12.03.2012-15.03.2012)

: GA102/09/1278, GA ČR

: tensor decomposition, pattern analysis, structural complexity

: 10.1007/978-3-642-28551-6_37

: http://library.utia.cas.cz/separaty/2012/SI/tichavsky-on revealing replicating structures in multiway data a novel tensor decomposition approach.pdf

(eng): A novel tensor decomposition is proposed to make it possible to identify replicating structures in complex data, such as textures and patterns in music spectrograms. In order to establish a computational framework for this paradigm, we adopt a multiway (tensor) approach. To this end, a novel tensor product is introduced, and the subsequent analysis of its properties shows a perfect match to the task of identification of recurrent structures present in the data. Out of a whole class of possible algorithms, we illuminate those derived so as to cater for orthogonal and nonnegative patterns. Simulations on texture images and a complex music sequence confirm the benefits of the proposed model and of the associated learning algorithms.

: BB