SOTAVerified

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

Recently AddedMost HypedMost ActiveNeeds VerificationMost Verified

Showing 151–175 of 211 papers

TitleStatusHype
Towards Human Pulse Rate Estimation from Face Video: Automatic Component Selection and Comparison of Blind Source Separation Methods—0
Towards Unsupervised Single-Channel Blind Source Separation using Adversarial Pair Unmix-and-Remix—0
Blind Source Separation in Polyphonic Music Recordings Using Deep Neural Networks Trained via Policy Gradients—0
Unsupervised Sparse Unmixing of Atmospheric Trace Gases from Hyperspectral Satellite Data—0
Unsupervised training of a deep clustering model for multichannel blind source separation—0
Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data—0
Variational Component Decoder for Source Extraction from Nonlinear Mixture—0
Wideband photonic blind source separation with optical pulse sampling—0
A computationally efficient semi-blind source separation based approach for nonlinear echo cancellation based on an element-wise iterative source steering—0
Broadband physical layer cognitive radio with an integrated photonic processor for blind source separation—0
A deep learning pipeline for identification of motor units in musculoskeletal ultrasound—0
A Deep Learning Technique using Low Sampling rate for residential Non Intrusive Load Monitoring—0
A Hypothesis Testing Approach to Nonstationary Source Separation—0
Analysis Co-Sparse Coding for Energy Disaggregation—0
A Neural Network for Determination of Latent Dimensionality in Nonnegative Matrix Factorization—0
A New Non-Negative Matrix Factorization Approach for Blind Source Separation of Cardiovascular and Respiratory Sound Based on the Periodicity of Heart and Lung Function—0
An Exploration of Optimal Parameters for Efficient Blind Source Separation of EEG Recordings Using AMICA—0
A Normative and Biologically Plausible Algorithm for Independent Component Analysis—0
A Novel CMB Component Separation Method: Hierarchical Generalized Morphological Component Analysis—0
An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks—0
Application of independent component analysis and TOPSIS to deal with dependent criteria in multicriteria decision problems—0
A probabilistic model for learning in cortical microcircuit motifs with data-based divisive inhibition—0
A RobustICA Based Algorithm for Blind Separation of Convolutive Mixtures—0
A Robustness Analysis of Blind Source Separation—0
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems—0
Show:102550
← PrevPage 7 of 9Next →

No leaderboard results yet.