神经网络BP算法在有源消声中的应用

为了克服传统自适应有源消声算法在应用中稳定性方面的不足，尝试将神经网络反向传播（ＢＰ）算法应用于有源消声技术。文中建立了基于ＢＰ算法的自适应有源消声（ＡＡＮＣ—ＢＰ）模型并给出该算法的递推公式。利用ＴＭＳ３２０Ｃ２５开发板实现了该算法功能。在半消声室中进行了单频和１００Ｈｚ带宽的消声实验，仅利用单个次级源结构便获得较好的消声效果。实验证明，基于ＢＰ算法的消声系统具有良好的稳定性。

Neural Network BP Algorithm Applied to Adaptive Active Noise Control

The traditional adaptive active noise control (AANC) models that we know appear to be not quite satisfactory in robustness. We applied neural network BP (back-propagation) algorithm to improving its robustness. Fig.1 shows our AANC-BP sound attenuation model. We derived eqs.(1) through (8) for this model. In a semi-anechoic chamber, we obtained some sound reduction experimental data for a single frequency noise (Fig.3a) and for a 100 Hz bandwidth noise (Fig.3b), using our AANC-BP control system. Fig.3 was based on the use of only a single secondary source for suppressing noise. We observed an increase in robustness.