A comprehensive survey on blind source separation for wireless adaptive processing: Principles, perspectives, challenges and new research directions
Z Luo, C Li, L Zhu - IEEE Access, 2018 - ieeexplore.ieee.org
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 …
increasingly crowded, and the interferences and composite signals will be ubiquitous in the …
Estimation of the complex‐valued mixing matrix by single‐source‐points detection with less sensors than sources
H Li, Y Shen, J Wang, X Ren - Transactions on Emerging …, 2012 - Wiley Online Library
This paper essentially considers the direction‐of‐arrival (DOA) estimation of far‐field source
signals in the underdetermined blind separation, where the mixing matrix is complex …
signals in the underdetermined blind separation, where the mixing matrix is complex …
Blind adaptive beamforming for cyclostationary signals: a subspace projection approach
JH Lee, CC Huang - IEEE Antennas and Wireless Propagation …, 2009 - ieeexplore.ieee.org
In this letter, we present an efficient method for blind adaptive beamforming with
cyclostationary signals. In comparison with the SCORE algorithms of Agee et al.(Proc. IEEE …
cyclostationary signals. In comparison with the SCORE algorithms of Agee et al.(Proc. IEEE …
Three-Level Distributed Real-Time Monitoring of Construction near Underground Infrastructure Using a Combined Intelligent Method
B Zhou, Y Gui, X Wang, X Xie - Sensors, 2022 - mdpi.com
With the rapid development of underground infrastructure and the uncertainty of its location,
the possibility of damage due to nearby construction has increased. Thus, for the early …
the possibility of damage due to nearby construction has increased. Thus, for the early …
[PDF][PDF] An optimal MMSE fuzzy predictor for SISO and MIMO blind equalization
The present work deals with the research of optimal solutions in unsupervised and nonlinear
signal processing. The proposed framework is based on nonlinear prediction, to be …
signal processing. The proposed framework is based on nonlinear prediction, to be …