In this work, we obtain sufficient conditions for the “stability” of our recently proposed algorithms, Least Squares Compressive Sensing residual (LS-CS) and modified-CS, for recursively reconstructing sparse signal sequences from noisy measurements. By “stability” we mean that the number of misses from the current support estimate and the number of extras in it remain bounded by a time-invaria...

Sparse signal representations have emerged as powerful tools in signal processing theory and applications, and serve as the basis of the now-popular field of compressive sensing (CS). However, several practical signal ensembles exhibit additional, richer structure beyond mere sparsity. Our particular focus in this paper is on signals and images where, owing to physical constraints, the position...