Nowlin WC, Guthart GS, Toth GK
SRI International, Menlo Park, California 94025, USA.
J Acoust Soc Am. 2000 Apr;107(4):2049-60. doi: 10.1121/1.428555.
Many real-world applications of active noise control are characterized by transfer functions that vary significantly and unpredictably. The controller's transfer-function models must adapt to these variations. Presented here is a class of adaptive filters that accomplish quasiperiodic system identification updates for feedforward control by using blocks of input-output histories. The algorithms form a one-dimensional family linking normalized least-mean squares (LMS) adaptive filters and block recursive least-squares, termed "block projection" algorithms, and generalize the noninvasive system identification studied by Sommerfeldt and Tichy. The system identification proceeds noninvasively, producing nonparametric impulse responses. Simulations show that the algorithm's convergence is faster than that of normalized LMS, even after the additional overhead of computing the update is taken into account. Both the multichannel generalization and application of these algorithms to system identification are novel. Simulations of the algorithms' performance using measured data are presented here, while experimental results of an implemented algorithm are contained in the companion paper.
有源噪声控制的许多实际应用都具有显著且不可预测变化的传递函数。控制器的传递函数模型必须适应这些变化。本文介绍了一类自适应滤波器，它通过使用输入 - 输出历史块来完成前馈控制的准周期系统识别更新。这些算法形成了一个一维族，将归一化最小均方（LMS）自适应滤波器和块递归最小二乘法联系起来，称为“块投影”算法，并推广了Sommerfeldt和Tichy所研究的非侵入式系统识别。系统识别以非侵入方式进行，产生非参数脉冲响应。仿真表明，即使考虑到计算更新的额外开销，该算法的收敛速度也比归一化LMS更快。这些算法的多通道推广及其在系统识别中的应用都是新颖的。本文给出了使用实测数据对算法性能进行的仿真，而配套论文中包含了所实现算法的实验结果。
