With radio frequency identification (RFID) becoming a popular wireless technology, more
and more relevant applications are emerging. Therefore, anti-collision algorithms, which …

With the rapid proliferation of wireless services, the frequency spectrum has become
increasingly crowded, and the interferences and composite signals will be ubiquitous in the …

In recent years, deep autoencoder networks (DANs) have shown enormous potential to
achieve state-of-the-art performance for recognizing multi-element geochemical anomalies …

Radio-frequency (RF) energy harvesting is a promising technology for Internet-of-Things
(IoT) devices to power sensors and prolong battery life. In this paper, we present a novel …

Blind source separation (BSS) is a well-known signal processing tool which is used to solve
practical data analysis problems in various fields of science. In BSS, we assume that the …

The continuous integration of fluctuating distributed generators and nonlinear power
electronic equipment have produced severe signal contamination and induced various …

This work proposes a framework to discover the topology of a non-collaborative packet-
based wireless network using radio-frequency (RF) sensors. The methodology developed is …

This contribution conceptualizes a blind source separation (BSS) model to recover sources
of geochemical signals such that multi-depth ore-related enrichment patterns in complex …

Joint blind source separation (JBSS) is a powerful methodology for analyzing multiple
related datasets, able to jointly extract sources that describe statistical dependencies across …

Snow avalanches impose a considerable threat to infrastructure and human safety in snow
bound mountain areas. Nevertheless, the spatial prediction of snow avalanches has …