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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

Showing 8190 of 211 papers

TitleStatusHype
Photonic Interference Cancellation with Hybrid Free Space Optical Communication and MIMO Receiver0
Modifications of FastICA in Convolutive Blind Source Separation0
Wideband photonic blind source separation with optical pulse sampling0
Blind Source Separation in Polyphonic Music Recordings Using Deep Neural Networks Trained via Policy Gradients0
Robust Blind Source Separation by Soft Decision-Directed Non-Unitary Joint Diagonalization0
Online Self-Attentive Gated RNNs for Real-Time Speaker Separation0
Drum-Aware Ensemble Architecture for Improved Joint Musical Beat and Downbeat TrackingCode1
Independent mechanism analysis, a new concept?Code1
More Behind Your Electricity Bill: a Dual-DNN Approach to Non-Intrusive Load Monitoring0
A Hypothesis Testing Approach to Nonstationary Source Separation0
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