Sparse Component Analysis: A General Framework for Linear and Nonlinear Blind Source Separation and Mixture Identification
- 22 May 2014
- book chapter
- Published by Springer Nature
- p. 151-196
Abstract
No abstract availableKeywords
This publication has 36 references indexed in Scilit:
- An algorithm for mixing matrix estimation in instantaneous blind source separationSignal Processing, 2009
- Temporal and time-frequency correlation-based blind source separation methods. Part I: Determined and underdetermined linear instantaneous mixturesSignal Processing, 2007
- Time–frequency ratio-based blind separation methods for attenuated and time-delayed sourcesMechanical Systems and Signal Processing, 2005
- A time–frequency blind signal separation method applicable to underdetermined mixtures of dependent sourcesSignal Processing, 2005
- Blind Separation of Speech Mixtures via Time-Frequency MaskingIEEE Transactions on Signal Processing, 2004
- Spectral unmixingIEEE Signal Processing Magazine, 2002
- Wavelet zoom1999
- Adaptive blind separation of independent sources: A deflation approachSignal Processing, 1995
- Independent component analysis, A new concept?Signal Processing, 1994
- Time-frequency distributions-a reviewProceedings of the IEEE, 1989