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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 125 of 211 papers

TitleStatusHype
S^3 -- Semantic Signal SeparationCode2
Direction-Aware Adaptive Online Neural Speech Enhancement with an Augmented Reality Headset in Real Noisy Conversational EnvironmentsCode2
GPU-accelerated Guided Source Separation for Meeting TranscriptionCode1
Faster IVA: Update Rules for Independent Vector Analysis based on Negentropy and the Majorize-Minimize PrincipleCode1
Trash or Treasure? An Interactive Dual-Stream Strategy for Single Image Reflection SeparationCode1
Independent mechanism analysis, a new concept?Code1
Unrolling PALM for sparse semi-blind source separationCode1
Blind Source Separation of Single-Channel Mixtures via Multi-Encoder AutoencodersCode1
Drum-Aware Ensemble Architecture for Improved Joint Musical Beat and Downbeat TrackingCode1
Beam-Guided TasNet: An Iterative Speech Separation Framework with Multi-Channel OutputCode1
Unsupervised Composable Representations for AudioCode1
Directional Sparse Filtering using Weighted Lehmer Mean for Blind Separation of Unbalanced Speech MixturesCode1
Fetal ECG Extraction from Maternal ECG using Attention-based CycleGANCode1
Transformer-based Hand Gesture Recognition via High-Density EMG Signals: From Instantaneous Recognition to Fusion of Motor Unit Spike TrainsCode1
Joint deconvolution and unsupervised source separation for data on the sphereCode0
Latent Bayesian melding for integrating individual and population modelsCode0
Hierarchical Probabilistic Model for Blind Source Separation via Legendre TransformationCode0
A Lightweight Deep Exclusion Unfolding Network for Single Image Reflection RemovalCode0
Identification of Power System Oscillation Modes using Blind Source Separation based on Copula StatisticCode0
Modeling the Repetition-based Recovering of Acoustic and Visual Sources with Dendritic NeuronsCode0
DURRNet: Deep Unfolded Single Image Reflection Removal NetworkCode0
Gaussian-binary Restricted Boltzmann Machines on Modeling Natural Image StatisticsCode0
Blind Source Separation Using Mixtures of Alpha-Stable DistributionsCode0
Biologically-Plausible Determinant Maximization Neural Networks for Blind Separation of Correlated SourcesCode0
Target Speech Extraction Based on Blind Source Separation and X-vector-based Speaker Selection Trained with Data AugmentationCode0
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