The under-determined blind source separation (BSS) problem is usually solved using the sparse component analysis (SCA) technique. In SCA, the BSS is usually solved in two steps, w...
We show that the exact recovery of sparse perturbations on the coefficient matrix in overdetermined Least Squares problems is possible for a large class of perturbation structure...
The K-means clustering problem seeks to partition the columns of a data matrix in subsets, such that columns in the same subset are ‘close’ to each other. The co-clustering pr...
Evangelos E. Papalexakis, Nicholas D. Sidiropoulos
Due to multipath delay spread and relatively high sampling rate in OFDM systems, the channel estimation is formulated as a sparse recovery problem, where a hybrid compressed sensi...
A K∗ -sparse vector x∗ ∈ RN produces measurements via linear dimensionality reduction as u = Φx∗ + n, where Φ ∈ RM×N (M < N), and n ∈ RM consists of independent ...