The Compressive Sensing (CS) framework aims to ease the burden on analog-to-digital converters (ADCs) by reducing the sampling rate required to acquire and stably recover sparse s...
Laurent Jacques, Jason N. Laska, Petros Boufounos,...
Abstract. We consider the problem of encoding a graph with n vertices and m edges compactly supporting adjacency, neighborhood and degree queries in constant time in the log n-bit ...
We propose a “compressive” estimator of the Wigner-Ville spectrum (WVS) for time-frequency sparse, underspread, nonstationary random processes. A novel WVS estimator involving...
— The new theory of compressive sensing enables direct analog-to-information conversion of compressible signals at subNyquist acquisition rates. We develop new theory, algorithms...
Jason N. Laska, Sami Kirolos, Marco F. Duarte, Tam...
In this paper we introduce a new watermarking model combining a joint time frequency (TF) representation using the molecular matching pursuit (MMP) algorithm and a psychoacoustic ...