Abstract
Affine projection (AP) algorithms have been demonstrated to have faster convergence speeds than the conventional least mean square (LMS) algorithms. However, LMS algorithms exhibit smaller steady-state mean square errors (MSEs) when compared with affine projection (AP) algorithms. Recently, several authors have proposed alternative methods based on convex combinations to improve the steady-state MSE of AP algorithms, even with the increased computational cost from the simultaneous use of two filters. In this paper, we present an alternative method based on an affine projection-like (APL-I) algorithm and least mean square (LMS) algorithm to solve the ANC under stationary Gaussian noise environments. In particular, we propose a switching filter selection criteria to improve the steady-state MSE without increasing the computational cost when compared with existing models. Here, we validate the proposed strategy in a single and a multichannel system, with and without automatically adjusting the scaling factor of the APL-I algorithm. The results demonstrate that the proposed scheme exploits the best features of each filter (APL-I and LMS) to guarantee rapid convergence with a low steady-state MSE. Additionally, the proposed approach demands a low computational burden compared with existing convex combination approaches, which will potentially lead to the development of real-time ANC applications.
Highlights
In recent years, advanced adaptive algorithms have attracted much interest in the development of effective active noise control (ANC) systems [1,2]
We propose selection criteria that indicate when the coefficients must be updated by analyzing the state of the overall error signal ek (n), i.e., the selection criteria are determined by comparing the instantaneous error power with the steady-state mean square errors (MSEs) of the FXAPL-I algorithm, which is the faster filter
The proposed filtering scheme uses selection criteria that are based on the level of the error power of the combined filters and the steady-state MSE of the FXAPL-I algorithm to create an alternating switch for the adaptive filters, the computational cost of the proposed filtering scheme algorithms is slightly greater than the computational cost of the conventional filtering schemes, such as the FXAPL-I and filtered-x least mean square (FXLMS) algorithms
Summary
In recent years, advanced adaptive algorithms have attracted much interest in the development of effective active noise control (ANC) systems [1,2]. New alternatives to reduce the computational cost of the AP algorithms have been proposed. As a consequence, these new approaches potentially allow the construction of efficient ANC systems [4,5]. Algorithm, to significantly minimize the computational cost and maintain the high convergence speed compared with that of the conventional FXAP algorithms. Their proposed algorithm can be potentially used in ANC systems that require lower computational power compared to AP algorithms and to retain a high convergence speed when compared with existing approaches
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