A Time-Varying Approach for the Blind Source Separation of Linear Quadratic Mixtures

Alexandre Miccheleti Lucena, Kenji Nose Filho, Ricardo Suyama

DOI: 10.14209/sbrt.2025.1571157357

Evento: XLIII Simpósio Brasileiro de Telecomunicações e Processamento de Sinais (SBrT2025)

Keywords: blind source separation linear quadratic nonlinear mixtures independent componetn analysis

Abstract

This paper evaluates nonlinear blind source separation (NLBSS) methods by interpreting the linear-quadratic (LQ) model over a time-varying local linear approximation. Two complementary approaches are explored: decomposing LQ mixtures via local linear approximations and explicitly reformulating them as time-varying system. Simulations validate the method under three scenarios: single-trial separation, Monte Carlo analysis with random matrices, and robustness tests across nonlinearity levels. Results highlight the N-EASI-R algorithm's superior performance for all quadratic terms tested. The study proposes whether combining both strategies could enhance robustness, potentially bridging theory and practical BSS applications.

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