Blind Source Separation Techniques

Blind Source Separation Techniques is a research topic within Signal Processing. Science Explorer counts 43k research works in it since 1950. 9.8% of them reached the world's top 10% most cited for their field and year.

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.

• Independent Component Analysis
• Blind Separation
• Sparse Representation
• Signal Decomposition
• Convolutional Mixtures
• Biomedical Signals
• Frequency Domain
• Non-stationary Sources
• Natural Images
• Temporal Structure