Nowadays, a large amount of information has to be transmitted or processed. This implies
high-power processing, large memory density, and increased energy consumption. In …

In this modern world, a massive amount of data is processed and broadcasted daily. This
includes the use of high energy, massive use of memory space, and increased power use. In …

The acquisition of a discrete-time signal is an important part of a compressive sensing
problem. A high-accuracy algorithm that could bring better signal recovery performance is …

We present a normalization of the p‐norm. A compressive sensing criterion is proposed
using the normalized zero norm. Based on the method of Lagrange multipliers, we derive …

An improvement of the typical iterative hard thresholding (IHT) algorithm is presented by
means of least squares initialization. Unlike the initialization that assigns all zeros to the …

Distributed unmanned aerial vehicle (UAV) swarms are formed by multiple UAVs with
increased portability, higher levels of sensing capabilities, and more powerful autonomy …

The limited availability of spectrum resources has been growing into a critical problem in
wireless communications, remote sensing, and electronic surveillance, etc. To address the …

With the aim of speeding up the measurement time of Brillouin distributed sensors, the use
of compressive sensing (CS) has been recently proposed to reconstruct the Brillouin gain …

With the growing scarcity of spectrum resources, wideband spectrum sensing is necessary
to process a large volume of data at a high sampling rate. For some applications, only …

The electronic support (ES) receivers require wide instantaneous bandwidth as a result of a
wide‐frequency range of modern radar signals. Thus, analogue‐to‐digital converters …