基于无限脉冲响应滤波器的自适应滤波E型有源噪声控制算法
Adaptive ⅡR filtered-E algorithm for active noise control
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摘要: 相对于有限脉冲响应(FIR)滤波器,无限脉冲响应(ⅡR)滤波器由于其本身自有的零-极点结构,能以较低的阶数即可与系统模型匹配。因此在有源噪声控制(ANC)中,使用ⅡR滤波器可以大大节省计算量并能提高系统效率。自适应滤波U型最小均方差(FULMS)算法是目前常用的基于ⅡR滤波器的有源噪声控制算法,但该算法却不能保证全局收敛,这大大限制了该算法在有源噪声控制中的应用。本文提出一种新的基于ⅡR滤波器的自适应有源噪声控制算法——滤波E型最小均方差算法,该算法计算量相对于FULMS算法仅略有增加,但具有良好的全局收敛性,仿真结果表明该算法具有良好的降噪效果。Abstract: Compared to Finite Impulse Response (FIR) filters, Infinite Impulse Response (ⅡR) filters can match the system better with much fewer coefficients, and hence the computation Load is saved and the performance improves. Therefore, it is attractive to use ⅡR filters instead of FIR filters in Active Noise Control (ANC). However, Filtered-U LMS (FULMS) algorithm, the ⅡR filter-based algorithm commonly used so far cannot ensure global convergence. A new ⅡR filter based adaptive algorithm, which can ensure global convergence with computation load only slightly increasing, is proposed. The algorithm is called Filtered-E LMS (FELMS) algorithm since the error signal is filtered by a time-variant FIR filter. Simulation results show that the FELMS algorithm presents better performance than the FULMS algorithm.