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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 26–50 of 211 papers

TitleStatusHype
Determined BSS based on time-frequency masking and its application to harmonic vector analysis—0
Blind Demixing of Diffused Graph Signals—0
Blind nonnegative source separation using biological neural networks—0
A probabilistic model for learning in cortical microcircuit motifs with data-based divisive inhibition—0
Blind Source Separation Algorithms Using Hyperbolic and Givens Rotations for High-Order QAM Constellations—0
A unified method for super-resolution recovery and real exponential-sum separation—0
A Unified Bayesian View on Spatially Informed Source Separation and Extraction based on Independent Vector Analysis—0
An Exploration of Optimal Parameters for Efficient Blind Source Separation of EEG Recordings Using AMICA—0
Dialogue Enhancement in Object-based Audio -- Evaluating the Benefit on People above 65—0
Blind stain separation using model-aware generative learning and its applications on fluorescence microscopy images—0
Blind Source Separation with Optimal Transport Non-negative Matrix Factorization—0
AudioSlots: A slot-centric generative model for audio separation—0
A survey of unsupervised learning methods for high-dimensional uncertainty quantification in black-box-type problems—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
A Unifying View on Blind Source Separation of Convolutive Mixtures based on Independent Component Analysis—0
Data-Driven Source Separation Based on Simplex Analysis—0
Bayesian Non-Parametric Multi-Source Modelling Based Determined Blind Source Separation—0
Blind source separation of baseband RF communication signals using mixed-signal matrix multiplication circuit—0
Deep-RLS: A Model-Inspired Deep Learning Approach to Nonlinear PCA—0
Deep Sparse Coding for Non-Intrusive Load Monitoring—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
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