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. © 2007 Elsevier B.V. All rights reserved.
Shi, Z., & Zhang, C. (2007). Nonlinear innovation to blind source separation. Neurocomputing, 71(1–3), 406–410. https://doi.org/10.1016/j.neucom.2007.08.007