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blind source separation

Blind source separation (BSS) is a signal processing technique that aims to separate multiple source signals from a set of mixed signals, without any prior knowledge about the sources or the mixing process. The goal is to recover the original source signals from the observed mixtures, typically using statistical and computational methods. BSS has applications in various fields such as audio signal processing, image processing, and telecommunications. It is used to extract useful information from mixed signals and to improve the quality of the source signals.

Papers

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Showing 76–100 of 211 papers

TitleStatusHype
Unsupervised Sparse Unmixing of Atmospheric Trace Gases from Hyperspectral Satellite Data—0
Noninvasive Fetal Electrocardiography: Models, Technologies and Algorithms—0
Switching Independent Vector Analysis and Its Extension to Blind and Spatially Guided Convolutional Beamforming Algorithms—0
A Normative and Biologically Plausible Algorithm for Independent Component Analysis—0
A Deep Learning Technique using Low Sampling rate for residential Non Intrusive Load Monitoring—0
One to Multiple Mapping Dual Learning: Learning Multiple Sources from One Mixed Signal—0
Variational Component Decoder for Source Extraction from Nonlinear Mixture—0
Machine learning methods for modelling and analysis of time series signals in geoinformatics—0
HYPERION: Hyperspectral Penetrating-type Ellipsoidal Reconstruction for Terahertz Blind Source Separation—0
Temporally Nonstationary Component Analysis; Application to Noninvasive Fetal Electrocardiogram Extraction—0
Photonic Interference Cancellation with Hybrid Free Space Optical Communication and MIMO Receiver—0
Sub-Nyquist Sampling with Optical Pulses for Photonic Blind Source Separation—0
Modifications of FastICA in Convolutive Blind Source Separation—0
Wideband photonic blind source separation with optical pulse sampling—0
Blind Source Separation in Polyphonic Music Recordings Using Deep Neural Networks Trained via Policy Gradients—0
Robust Blind Source Separation by Soft Decision-Directed Non-Unitary Joint Diagonalization—0
Online Self-Attentive Gated RNNs for Real-Time Speaker Separation—0
More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring—0
A Hypothesis Testing Approach to Nonstationary Source Separation—0
Integration of deep learning with expectation maximization for spatial cue based speech separation in reverberant conditions—0
Joint Dereverberation and Separation with Iterative Source Steering—0
Blind stain separation using model-aware generative learning and its applications on fluorescence microscopy images—0
Independent Vector Extraction for Fast Joint Blind Source Separation and Dereverberation—0
Nonlinear Independent Component Analysis for Discrete-Time and Continuous-Time SignalsCode0
Blind Demixing of Diffused Graph Signals—0
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