A Variable Step-Size FxLMS Algorithm for Nonlinear Feedforward Active Noise Control DOI Creative Commons

Thi Trung Tin Nguyen,

Zhang Fa-xiang, Jing Na

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(8), P. 2569 - 2569

Published: April 18, 2025

Active noise control (ANC) represents an efficient technology for enhancing the suppression performance and ensuring stable operation of multi-sensor systems through generative model-enhanced data representation dynamic information fusion across heterogeneous sensors due to complexity real-world environment. To address problems caused by a nonlinear source, novel adaptive neuro-fuzzy network controller is proposed feedforward ANC based on variable step-size filtered-x least-mean-square (VSS-LMS) algorithm. Specifically, LMS algorithm first introduced update weight parameters network. Then, adjustment strategy calculate learning gain used in algorithm, which aims improve performance. Additionally, stability method proven discrete Lyapunov theorem. Extensive simulation experiments show that surpasses mainstream methods with regard noise.

Language: Английский

A Variable Step-Size FxLMS Algorithm for Nonlinear Feedforward Active Noise Control DOI Creative Commons

Thi Trung Tin Nguyen,

Zhang Fa-xiang, Jing Na

et al.

Sensors, Journal Year: 2025, Volume and Issue: 25(8), P. 2569 - 2569

Published: April 18, 2025

Active noise control (ANC) represents an efficient technology for enhancing the suppression performance and ensuring stable operation of multi-sensor systems through generative model-enhanced data representation dynamic information fusion across heterogeneous sensors due to complexity real-world environment. To address problems caused by a nonlinear source, novel adaptive neuro-fuzzy network controller is proposed feedforward ANC based on variable step-size filtered-x least-mean-square (VSS-LMS) algorithm. Specifically, LMS algorithm first introduced update weight parameters network. Then, adjustment strategy calculate learning gain used in algorithm, which aims improve performance. Additionally, stability method proven discrete Lyapunov theorem. Extensive simulation experiments show that surpasses mainstream methods with regard noise.

Language: Английский

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