Block sparse representations of tensors using kronecker bases

Cesar F. Caiafa, Andrzej Cichocki.

Serie: Trabajos publicados del IAR ; no. 1141

IEEE International Conference on Acoustics, Speech, and Signal Processing, 2012 (ICASSP 2012), 25-30 March, Kyoto, Japan.

Resumen: In this paper, we consider sparse representations of mul- tidimensional signals (tensors) by generalizing the onedimensional 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 nonzero 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 blocksparsity property obtaining faster and more precise sparse representations of tensors compared to the case of applying the classical OMP (Orthogonal Matching Pursuit).