In this paper, we consider sparse decomposition (SD) of twodimensional (2D) signals on overcomplete dictionaries with separable atoms. Although, this problem can be solved by conv...
Aboozar Ghafari, Massoud Babaie-Zadeh, Christian J...
Recently, the Sparse Matrix Transform (SMT) has been proposed as a tool for estimating the eigen-decomposition of high dimensional data vectors [1]. The SMT approach has two major...
Leonardo R. Bachega, Guangzhi Cao, Charles A. Boum...
Sparse sampling with coprime lattice arrays was introduced recently in the literature. It has been shown that a dense coarray can be constructed from such a pair of arrays, and is...
In underdetermined blind source separation problems, it is common practice to exploit the underlying sparsity of the sources for demixing. In this work, we propose two sparse decom...
The theory of compressive sampling involves making random linear projections of a signal. Provided signal is sparse in some basis, small number of such measurements preserves the ...