Article ID | Journal | Published Year | Pages | File Type |
---|---|---|---|---|
410838 | Neurocomputing | 2007 | 5 Pages |
Abstract
This letter proposes a blind source separation (BSS) method based on the nonlinear innovation of original sources. A simple algorithm is presented by minimizing a loss function of the nonlinear innovation. The method exploits the nonstationarity of sources in the sense that the variance of each source signal can be assumed to change smoothly as a function of time. Simulations verify the efficient implementation of the proposed method, especially its robustness to the outliers.
Related Topics
Physical Sciences and Engineering
Computer Science
Artificial Intelligence
Authors
Zhenwei Shi, Changshui Zhang,