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A Momentum Two-Gradient Direction Algorithm with Variable Step Size Applied to Solve Practical Output Constraint Issue for Active Noise Control by Xiaoyi Shen; Dongyuan Shi; Zhengding Luo; Junwei Ji; Woon-Seng Gan is a scholarly article available to read on EtoBox.

What is A Momentum Two-Gradient Direction Algorithm with Variable Step Size Applied to Solve Practical Output Constraint Issue for Active Noise Control about?

Active noise control (ANC) has been widely utilized to reduce unwanted environmental noise. The primary objective of ANC is to generate an anti-noise with the same amplitude but the opposite phase of the primary noise using the secondary source. However, the effectiveness of the ANC application is impacted by the speaker's output saturation. This paper proposes a two-gradient direction ANC algorithm with a momentum factor to solve the saturation with faster convergence. In order to make it implemented in real-time, a computation-effective variable step size approach is applied to further reduce the steady-state error brought on by the changing gradient directions. The time constant and step size bound for the momentum two-gradient direction algorithm is analyzed. Simulation results show that the proposed algorithm performs effectively in the time-unvaried and time-varied environment.

Author

Xiaoyi Shen; Dongyuan Shi; Zhengding Luo; Junwei Ji; Woon-Seng Gan

Publisher

IEEE

Published

2023

Language

EN