Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation. [PDF]
Nat Commun, 2023 The expansion of telecommunications incurs increasingly severe crosstalk and interference, and a physical layer cognitive method, called blind source separation (BSS), can effectively address these issues.
Zhang W +8 more
europepmc +3 more sources
A Blind Source Separation Method Based on Bounded Component Analysis Optimized by the Improved Beetle Antennae Search [PDF]
Sensors, 2023 Currently, the widely used blind source separation algorithm is typically associated with issues such as a sluggish rate of convergence and unstable accuracy, and it is mostly suitable for the separation of independent source signals.
Mingyang Tang, Yafeng Wu
doaj +2 more sources
Single-Channel Blind Source Separation of Spatial Aliasing Signal Based on Stacked-LSTM. [PDF]
Sensors (Basel), 2021 Aiming at the problem of insufficient separation accuracy of aliased signals in space Internet satellite-ground communication scenarios, a stacked long short-term memory network (Stacked-LSTM) separation method based on deep learning is proposed.
Zhao M +5 more
europepmc +2 more sources
Blind Source Separation Based on Double-Mutant Butterfly Optimization Algorithm [PDF]
Sensors, 2022 The conventional blind source separation independent component analysis method has the problem of low-separation performance. In addition, the basic butterfly optimization algorithm has the problem of insufficient search capability. In order to solve the
Qingyu Xia +5 more
doaj +2 more sources
Blind nonnegative source separation using biological neural networks [PDF]
Neural Computation, 2017 Blind source separation, i.e. extraction of independent sources from a mixture, is an important problem for both artificial and natural signal processing.
Chklovskii, Dmitri B. +2 more
core +2 more sources
A New Approach for Motor Imagery Classification Based on Sorted Blind Source Separation, Continuous Wavelet Transform, and Convolutional Neural Network. [PDF]
Sensors (Basel), 2019 Brain-Computer Interfaces (BCI) are systems that allow the interaction of people and devices on the grounds of brain activity. The noninvasive and most viable way to obtain such information is by using electroencephalography (EEG). However, these signals
Ortiz-Echeverri CJ +3 more
europepmc +2 more sources
Kernel-FastICA-Based Nonlinear Blind Source Separation for Anti-Jamming Satellite Communications [PDF]
SensorsSatellite communication systems, as a core component of global information infrastructure, have undergone unprecedented development. However, the open nature of satellite channels renders them vulnerable to electromagnetic interference, making anti ...
Xiya Sun, Changqing Li, Jiong Li, Qi Su
doaj +2 more sources
IEEE Access, 2018 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 wireless receiver.
Zhongqiang Luo, Chengjie Li, Lidong Zhu
doaj +2 more sources
Performance measurement in blind audio source separation
IEEE Transactions on Audio Speech and Language Processing, 2006 E. Vincent, R. Gribonval, C. Févotte
exaly +2 more sources
Unsupervised Blind Source Separation with Variational Auto-Encoders
European Signal Processing Conference, 2021 Supervised source separation requires expensive synthetic datasets containing clean, ground truth-source signals, while unsupervised separation requires only data mixtures.
Julian Neri, Roland Badeau, P. Depalle
semanticscholar +1 more source