In multiple attribute group decision-making (MAGDM), a consensus exists that the
psychological factors of decision makers (DMs) generally influence their choice of optimal …

Compressive sensing is used to recover a sparse signal from linear measurements. Without
any prior support information (PSI), least absolute shrinkage and selection operator …

In this paper, the hybrid Delay-And-Sum (DAS) with Sparse Reconstruction (SR) method
was further developed for damage location in composite plates. In composite materials …

Applications such as wireless communications require efficient sensing techniques of
signals with the a priori knowledge of those being lattice-valued. In this paper, we study the …

We study the problem of recovering a block-sparse signal from under-sampled observations.
The non-zero values of such signals appear in few blocks, and their recovery is often …

This paper considers the joint device activity detection and channel estimation problem in a
massive Internet of Things (IoT) connectivity system, where a large number of IoT devices …

To perform active structural health monitoring, guided Lamb waves for damage detection
have recently gained extensive attention. Many algorithms are used for damage detection …

In the future 6G integrated sensing and communication (ISAC) cellular systems, networked
sensing is a promising technique that can leverage the cooperation among the base stations …

In this paper, we propose a novel method based on sparse regularization with learnable
partition weights (LPWs) for bandwidth extrapolation (BWE) 2-D imaging of ultra-wideband …

Compressive sensing (CS) techniques for estimating the direction-of-arrival (DoA) stand
apart from traditional approaches due to their ability to derive DoA information from just a …