Sparse signals are characterized by a few nonzero coefficients in one of their transformation
domains. This was the main premise in designing signal compression algorithms …

Compressive Sensing, as an emerging technique in signal processing is reviewed in this
paper together with its common applications. As an alternative to the traditional signal …

Search and rescue (SAR) missions comprise search for, and provision of aid to people who
are in distress or imminent danger. Providing the best possible input for the planners and …

With rapid development of space platforms such as small satellites and UAVs for public
services, remote sensing services have been considered as one of the most promising …

Nonstationary signals, approximately sparse in the joint time-frequency domain, are
considered. Reconstruction of such signals with sparsity constraint is analyzed in this paper …

Search and rescue operations usually require significant resources, personnel, equipment,
and time. In order to optimize the resources and expenses and to increase the efficiency of …

A precise and accurate monitoring of different parameters such as temperature, relative
humidity or gas level, in cold chain logistic, is important for preserving the quality of the …

Sparse signals, assuming a small number of nonzero coefficients in a transformation
domain, can be reconstructed from a reduced set of measurements. In practical applications …

In the unmanned aerial vehicle-based wireless sensor network, the compressive sensing
approach can simultaneously locate multiple ground radio frequency sources, while the …

In this paper, the sampling rate of traditional signal reconstruction should be more than 2
times the maximum frequency of the original signal in order to ensure the non-distortion …