BLOCK SPARSE REPRESENTATIONS OF TENSORS USING KRONECKER BASES

CESAR F. CAIAFA; ANDRZEJ CICHOCKI

Kyoto

Conferencia; ICASSP 2012, IEEE International Conference on Acoustics, Speech and Signal Processing; 2012

Kyoto University

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 (OrthogonalMatching Pursuit).