Blind Source Separation Techniques
Description: This cluster of papers focuses on blind source separation and independent component analysis, with applications in signal decomposition, biomedical signals, and processing of convolutive mixtures. The methods often utilize sparse representation and exploit the temporal structure of the signals, particularly in the frequency domain.
Characteristic keywords: blind source separation, independent component analysis, FastICA, signal separation, convolutive mixtures, mixing matrix estimation, underdetermined blind source separation, source number estimation, independent vector analysis, joint diagonalization, linear mixtures, instantaneous mixing, contrast function, nonlinear blind source separation, non-stationary sources, second-order blind identification, convolutive blind source separation, permutation problem, instantaneous mixtures, non-Gaussian sources, sparse component analysis, Infomax, image separation, nonlinear mixtures, blind source extraction
Sibling topics: Video Coding and Compression Technologies, Biometric Identification and Security, Speech and Audio Processing, Direction-of-Arrival Estimation Techniques, Digital Filter Design and Implementation, Data Management and Algorithms, Advanced Malware Detection Techniques, Music and Audio Processing, Time Series Analysis and Forecasting
Parent subfield: Signal Processing
Field: Computer Science
Domain: Physical Sciences
OpenAlex ID: T11447