Improving convergence in finite word length nonlinear active noise control systems

Abstract

An attempt has been made in this paper to improve the convergence of functional link artificial neural network (FLANN) based nonlinear active noise control (ANC) systems. This improvement has been achieved by formulating a recursive least square (RLS) training mechanism. However, FLANN-RLS ANC systems are not effective in noise mitigation when implemented… (More)
DOI: 10.1109/ICDSP.2015.7251936

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