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Secondary path modeling for narrowband active noise control systems

机译:窄带有源噪声控制系统的次级路径建模

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摘要

This work examines the performance of both offline and online secondary path modeling algorithms that are used in narrowband active noise control (NANC) systems. Theoretical analysis reveals that disturbances that are sensed by error sensors reduce the convergence rate and accuracy of adaptive system identification. In a parallel structure narrowband active noise control system, a filterbank is applied to partition the full-band excitation and error signals to utilize an independent and lower-order secondary-path modeling filter for every channel. This method increases convergence speed and modeling accuracy. The results of an analysis and improved performance are confirmed by simulations in which measured transfer functions are used.
机译:这项工作检查了在窄带有源噪声控制(NANC)系统中使用的离线和在线辅助路径建模算法的性能。理论分析表明,误差传感器感应到的干扰会降低自适应系统识别的收敛速度和准确性。在并行结构的窄带有源噪声控制系统中,滤波器组用于划分全带激励和误差信号,以便为每个通道使用独立的低阶次级路径建模滤波器。该方法提高了收敛速度和建模精度。分析的结果和改进的性能通过使用测量的传递函数的仿真得到了证实。

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