Functional Link Adaptive Filters for Nonlinear Acoustic Echo Cancellation

• Published in: IEEE transactions on audio, speech, and language processing speech, and language processing, 2013-07, Vol.21 (7), p.1502-1512
• Main Authors: Comminiello, D., Scarpiniti, M., Azpicueta-Ruiz, L. A., Arenas-Garcia, J., Uncini, A.
• Format: Article
• Language: English
• Subjects: Acoustics; Adaptation models; Adaptive filters; Applied sciences; Architecture; Cancellation; collaborative adaptive filters; Computational modeling; Computer architecture; Detection, estimation, filtering, equalization, prediction; Exact sciences and technology; Functional links; Information, signal and communications theory; Links; Miscellaneous; nonlinear acoustic echo cancellation; nonlinear channel modeling; Nonlinearity; Robustness; Signal and communications theory; Signal processing; Signal, noise; Studies; Telecommunications and information theory; Transaction processing; Vectors
• ISSN: 1558-7916; 2329-9290; 1558-7924; 2329-9304
• DOI: 10.1109/TASL.2013.2255276

This paper introduces a new class of nonlinear adaptive filters, whose structure is based on Hammerstein model. Such filters derive from the functional link adaptive filter (FLAF) model, defined by a nonlinear input expansion, which enhances the representation of the input signal through a projection in a higher dimensional space, and a subsequent adaptive filtering. In particular, two robust FLAF-based architectures are proposed and designed ad hoc to tackle nonlinearities in acoustic echo cancellation (AEC). The simplest architecture is the split FLAF, which separates the adaptation of linear and nonlinear elements using two different adaptive filters in parallel. In this way, the architecture can accomplish distinctly at best the linear and the nonlinear modeling. Moreover, in order to give robustness against different degrees of nonlinearity, a collaborative FLAF is proposed based on the adaptive combination of filters. Such architecture allows to achieve the best performance regardless of the nonlinearity degree in the echo path. Experimental results show the effectiveness of the proposed FLAF-based architectures in nonlinear AEC scenarios, thus resulting an important solution to the modeling of nonlinear acoustic channels.