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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
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
AudioSlots: A slot-centric generative model for audio separation—0
A Unified Bayesian View on Spatially Informed Source Separation and Extraction based on Independent Vector Analysis—0
A unified method for super-resolution recovery and real exponential-sum separation—0
A Unifying View on Blind Source Separation of Convolutive Mixtures based on Independent Component Analysis—0
Bayesian Non-Parametric Multi-Source Modelling Based Determined Blind Source Separation—0
Blind Demixing of Diffused Graph Signals—0
Blind nonnegative source separation using biological neural networks—0
Blind Source Separation Algorithms Using Hyperbolic and Givens Rotations for High-Order QAM Constellations—0
Blind Source Separation for Mixture of Sinusoids with Near-Linear Computational Complexity—0
Blind Source Separation for NMR Spectra with Negative Intensity—0
Blind Source Separation: Fundamentals and Recent Advances (A Tutorial Overview Presented at SBrT-2001)—0
Blind Source Separation in Biomedical Signals Using Variational Methods—0
Blind source separation of baseband RF communication signals using mixed-signal matrix multiplication circuit—0
Blind Source Separation with Optimal Transport Non-negative Matrix Factorization—0
Blind stain separation using model-aware generative learning and its applications on fluorescence microscopy images—0
Cocktail Party Attack: Breaking Aggregation-Based Privacy in Federated Learning using Independent Component Analysis—0
Consistent ICA: Determined BSS meets spectrogram consistency—0
Convergent Bayesian formulations of blind source separation and electromagnetic source estimation—0
Convex Analysis of Mixtures for Separating Non-negative Well-grounded Sources—0
基於稀疏成份分析之旋積盲訊號源分離方法 (Convolutive Blind Source Separation Based on Sparse Component Analysis) [In Chinese]—0
Data-Driven Source Separation Based on Simplex Analysis—0
Deep Learning for RF Signal Classification in Unknown and Dynamic Spectrum Environments—0
Deep-RLS: A Model-Inspired Deep Learning Approach to Nonlinear PCA—0
Deep Sparse Coding for Non-Intrusive Load Monitoring—0
Determined BSS based on time-frequency masking and its application to harmonic vector analysis—0
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