This paper addresses the issue of robust sparse recovery in compressive sensing (CS) in
the presence of impulsive measurement noise. Recently, robust data-fitting models, such as …

This paper addresses the robust reconstruction problem of a sparse signal from compressed
measurements. We propose a robust formulation for sparse reconstruction that employs the …

Greedy pursuit, which includes matching pursuit (MP) and orthogonal matching pursuit
(OMP), is an efficient approach for sparse approximation. However, conventional greedy …

In this article, a continuous-time complex-valued projection neural network (CCPNN) in a
matrix state space is first proposed for a general complex-variable basis pursuit problem …

Abstract Background and Objective: Fluorescence molecular tomography (FMT) is a non-
invasive molecular imaging modality that can be used to observe the three-dimensional …

Distributed compressed sensing techniques are applied to enhance sparse channel
estimation performance in underwater acoustic multiband systems. The core idea is to use …

Much research has been devoted to complex-variable optimization problems due to their
engineering applications. However, the complex-valued optimization method for solving …

Sensor-based online process monitoring has extensive applications, such as in
manufacturing and service industries. In real environments, though, sensor data are often …

Many approaches have been studied in the field of array signal processing when impulsive
noise is modeled with an alpha-stable distribution. By introducing the correntropy, which …

The impulsive noise can deteriorate sharply the performance of orthogonal frequency
division multiplexing (OFDM) systems. In this paper, we propose a novel joint channel …