Improving performance of FxRLS algorithm for active noise control of impulsive noise

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• 作者：Ayesha Zeb ; ^{ayeshazeb79@ee.ceme.edu.pk" class="auth_mail" title="E-mail the corresponding author} ; Alina Mirza ; Qasim Umar Khan ; Shahzad A. Sheikh
• 关键词：Active noise control ; Impulsive noise ; Stable distributions ; FxRLS algorithm
• 刊名：Applied Acoustics
• 出版年：2017
• 出版时间：15 January 2017
• 年：2017
• 卷：116
• 期：Complete
• 页码：364-374
• 全文大小：2375 K

文摘

Active noise control (ANC) systems employing adaptive filters suffer from stability issues in the presence of impulsive noise. New impulsive noise control algorithms based on filtered-x recursive least square (FxRLS) algorithm are presented. The FxRLS algorithm gives better convergence than the filtered-x least mean square (FxLMS) algorithm and its variants but lacks robustness in the presence of high impulsive noise. In order to improve the robustness of FxRLS algorithm for ANC of impulsive noise, two modifications are suggested. First proposed modification clips the reference and error signals while, the second modification incorporates energy of the error signal in the gain of FxRLS (MGFxRLS) algorithm. The results demonstrate improved stability and robustness of proposed modifications in the FxRLS algorithm. However, another limitation associated with the FxRLS algorithm is its computationally complex nature. In order to reduce the computational load, a hybrid algorithm based on proposed MGFxRLS and normalized step size FxLMS (NSS-FXLMS) is also developed in this paper. The proposed hybrid algorithm combines the stability of NSS-FxLMS algorithm with the fast convergence speed of the proposed MGFxRLS algorithm. The results of the proposed hybrid algorithm prove that its convergence speed is faster than that of NSS-FxLMS algorithm with computational complexity lesser than that of FxRLS algorithm.