Abstract
In this paper we propose a filter combination for the adaptive noise cancellation (ANC) problem in nonlinear environment. The architecture consists in a convex combination of two adaptive filters: a classical filter and a nonlinear filter based on Functional Links. While the convergence of the linear filter is very fast, the convergence of the nonlinear one might be slower, even if it provides a more accurate solution. The convex combination of both filters allows to reach good performances in terms of convergence and speed. In addition a variable step size is used in order to obtain better performance. Several experimental results, in different reverberant conditions, demonstrate the effectiveness of the proposed approach.
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Scarpiniti, M., Comminiello, D., Parisi, R., Uncini, A. (2013). A Collaborative Filter Approach to Adaptive Noise Cancellation. In: Apolloni, B., Bassis, S., Esposito, A., Morabito, F. (eds) Neural Nets and Surroundings. Smart Innovation, Systems and Technologies, vol 19. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-35467-0_11
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DOI: https://doi.org/10.1007/978-3-642-35467-0_11
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