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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 101–125 of 211 papers

TitleStatusHype
Time Series Source Separation with Slow Flows—0
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
Frequency domain TRINICON-based blind source separation method with multi-source activity detection for sparsely mixed signals—0
Generalized Canonical Correlation Analysis and Its Application to Blind Source Separation Based on a Dual-Linear Predictor Structure—0
Generalized Fast Multichannel Nonnegative Matrix Factorization Based on Gaussian Scale Mixtures for Blind Source Separation—0
Generalized Non-orthogonal Joint Diagonalization with LU Decomposition and Successive Rotations—0
Gradient of Probability Density Functions based Contrasts for Blind Source Separation (BSS)—0
Group Component Analysis for Multiblock Data: Common and Individual Feature Extraction—0
Heuristics for Efficient Sparse Blind Source Separation—0
High-Throughput Blind Co-Channel Interference Cancellation for Edge Devices Using Depthwise Separable Convolutions, Quantization, and Pruning—0
How secure is the time-modulated array-enabled ofdm directional modulation?—0
HYPERION: Hyperspectral Penetrating-type Ellipsoidal Reconstruction for Terahertz Blind Source Separation—0
HyperKING: Quantum-Classical Generative Adversarial Networks for Hyperspectral Image Restoration—0
Implementation of fast ICA using memristor crossbar arrays for blind image source separations—0
Improved Differentially Private Decentralized Source Separation for fMRI Data—0
Independent Component Analysis by Entropy Maximization with Kernels—0
Independent Vector Analysis via Log-Quadratically Penalized Quadratic Minimization—0
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