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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 151–200 of 211 papers

TitleStatusHype
Towards Human Pulse Rate Estimation from Face Video: Automatic Component Selection and Comparison of Blind Source Separation Methods—0
Semi-blind source separation with multichannel variational autoencoderCode0
On the achievability of blind source separation for high-dimensional nonlinear source mixturesCode0
Scalable Convolutional Dictionary Learning with Constrained Recurrent Sparse Auto-encodersCode0
Signals as Parametric Curves: Application to Independent Component Analysis and Blind Source Separation—0
Sparse Pursuit and Dictionary Learning for Blind Source Separation in Polyphonic Music RecordingsCode0
An Unsupervised Approach to Solving Inverse Problems using Generative Adversarial Networks—0
Trace your sources in large-scale data: one ring to find them allCode0
Data-Driven Source Separation Based on Simplex Analysis—0
Frequency domain TRINICON-based blind source separation method with multi-source activity detection for sparsely mixed signals—0
Blind Source Separation with Optimal Transport Non-negative Matrix Factorization—0
Multiple component decomposition from millimeter single-channel data—0
Blind Source Separation Using Mixtures of Alpha-Stable DistributionsCode0
Fast and Scalable Distributed Deep Convolutional Autoencoder for fMRI Big Data Analytics—0
Elliptical modeling and pattern analysis for perturbation models and classfication—0
A unified method for super-resolution recovery and real exponential-sum separation—0
A probabilistic model for learning in cortical microcircuit motifs with data-based divisive inhibition—0
Blind nonnegative source separation using biological neural networks—0
Discovery and visualization of structural biomarkers from MRI using transport-based morphometry—0
Inertia-Constrained Pixel-by-Pixel Nonnegative Matrix Factorisation: a Hyperspectral Unmixing Method Dealing with Intra-class Variability—0
Strongly-Typed Agents are Guaranteed to Interact Safely—0
Double Coupled Canonical Polyadic Decomposition for Joint Blind Source Separation—0
Sequence-to-point learning with neural networks for nonintrusive load monitoringCode0
Nonnegative Matrix Factorization for identification of unknown number of sources emitting delayed signals—0
Spatio-temporal Dynamics of Intrinsic Networks in Functional Magnetic Imaging Data Using Recurrent Neural Networks—0
Independent Component Analysis by Entropy Maximization with Kernels—0
Enhancing ICA Performance by Exploiting Sparsity: Application to FMRI Analysis—0
Variational Mixture Models with Gamma or inverse-Gamma componentsCode0
Sifting Common Information from Many VariablesCode0
Effective Blind Source Separation Based on the Adam Algorithm—0
Joint Sound Source Separation and Speaker Recognition—0
Variational Autoencoders for Feature Detection of Magnetic Resonance Imaging Data—0
Blind Source Separation: Fundamentals and Recent Advances (A Tutorial Overview Presented at SBrT-2001)—0
Robust Heart Rate Measurement From Video Using Select Random Patches—0
Latent Bayesian melding for integrating individual and population modelsCode0
Robust Sparse Blind Source Separation—0
Blind Source Separation Algorithms Using Hyperbolic and Givens Rotations for High-Order QAM Constellations—0
Gradient of Probability Density Functions based Contrasts for Blind Source Separation (BSS)—0
Non-parametric Bayesian Models of Response Function in Dynamic Image Sequences—0
Convergent Bayesian formulations of blind source separation and electromagnetic source estimation—0
Difficulties applying recent blind source separation techniques to EEG and MEG—0
Sparsity and adaptivity for the blind separation of partially correlated sourcesCode0
Signal Aggregate Constraints in Additive Factorial HMMs, with Application to Energy Disaggregation—0
Estimating the intrinsic dimension in fMRI space via dataset fractal analysis - Counting the `cpu cores' of the human brain—0
A RobustICA Based Algorithm for Blind Separation of Convolutive Mixtures—0
NMF with Sparse Regularizations in Transformed DomainsCode0
Kernel Nonnegative Matrix Factorization Without the Curse of the Pre-image - Application to Unmixing Hyperspectral Images—0
Convex Analysis of Mixtures for Separating Non-negative Well-grounded Sources—0
Generalized Canonical Correlation Analysis and Its Application to Blind Source Separation Based on a Dual-Linear Predictor Structure—0
Phase transitions and sample complexity in Bayes-optimal matrix factorization—0
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