Snapshot compressed sensing (CS) refers to compressive imaging systems in which
multiple frames are mapped into a single measurement frame. Each pixel in the acquired …

Moving force identification (MFI) techniques have been widely studied in recent years.
However, the contradiction between response acquisition and energy consumption limits …

Abstract Conventional Compressive Sampling (CS)-based data aggregation methods
require a large number of sensor nodes for each CS measurement leading to an inefficient …

Compressive Sensing (CS) exploits the surprising fact that the information contained in a
sparse signal can be preserved in a small number of compressive, often random linear …

In this paper, a new compressive sampling-based image coding scheme is developed to
achieve competitive coding efficiency at lower encoder computational complexity, while …

Recently, the chaotic compressive sensing paradigm has been widely used in many areas,
due to its ability to reduce data acquisition time with high security. For cognitive radio …

Sampling of signals defined over the nodes of a graph is one of the crucial problems in
graph signal processing, whereas in classical signal processing, sampling is a well-defined …

Parallel acquisition systems arise in various applications to moderate problems caused by
insufficient measurements in single-sensor systems. These systems allow simultaneous …

This paper offers a characterization of fundamental limits on the classification and
reconstruction of high-dimensional signals from low-dimensional features, in the presence of …

Delay-coordinate mapping is an effective and widely used technique for reconstructing and
analyzing the dynamics of a nonlinear system based on time-series outputs. The efficacy of …