Block sparse representations of tensors using Kronecker bases

Cesar F. Caiafa, Andrzej Cichocki

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

37 Citations (Scopus)

Abstract

In this paper, we consider sparse representations of multidimensional signals (tensors) by generalizing the one-dimensional case (vectors). A new greedy algorithm, namely the Tensor-OMP algorithm, is proposed to compute a block-sparse representation of a tensor with respect to a Kronecker basis where the non-zero coefficients are restricted to be located within a sub-tensor (block). It is demonstrated, through simulation examples, the advantage of considering the Kronecker structure together with the block-sparsity property obtaining faster and more precise sparse representations of tensors compared to the case of applying the classical OMP (Orthogonal Matching Pursuit).

Original languageEnglish
Title of host publication2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Proceedings
Pages2709-2712
Number of pages4
DOIs
Publication statusPublished - 2012
Externally publishedYes
Event2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012 - Kyoto, Japan
Duration: 25 Mar 201230 Mar 2012

Publication series

NameICASSP, IEEE International Conference on Acoustics, Speech and Signal Processing - Proceedings
ISSN (Print)1520-6149

Conference

Conference2012 IEEE International Conference on Acoustics, Speech, and Signal Processing, ICASSP 2012
Country/TerritoryJapan
CityKyoto
Period25/03/1230/03/12

Keywords

  • Kronecker Bases
  • Orthogonal Matching Pursuit (OMP)
  • Sparse Representations
  • Tensors

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