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噪声有源控制的人工神经网络方法 被引量:16

Active Noise Control Using an artificial Neural Network
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摘要 讨论了有源噪声控制(ANC)问题,提出了一种基于人工神经网络的非线性噪声有源自适应控制方法,给出了一种基于误差梯度下降的学习算法,证明了闭环控制系统在Lyapunov意义下的稳定性。 The active noise control(ANC) is studied. If the primary noise path were nonlinear,the control system based on adaptive filter technology would be invalid. An adaptive active nonlinear noise control approach using a neural network is derived. A learning algorithm based on the error gradient descent method is proposed. The stability of closed loop system is proved in the Lyapunov's sense. A nonlinear simulation example is given to show that the adaptive active noise control method based on a neural network is very efficient to the noninear noise control.
出处 《电声技术》 北大核心 2000年第7期24-26,共3页 Audio Engineering
基金 北京市教委资助科技项目!99KJ44
关键词 有源噪声控制 人工神经网络 非线性系统 Active noise control artificial neural network nonlinear system
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参考文献3

  • 1[1]Elliott S J and Nelson P A. Active Noise Control. IEEE Signal Process Mag.1993 10 4 12-35 被引量:1
  • 2[2]Chao Chee Ku and Kwang Y Lee.Diagonal Recurrent Neural Networks for Dynamic Systems Conrtol. IEEE Trans on Neural Networks 1995 6 1 144-156. 被引量:1
  • 3[3]David H C and Robert W S.Adaptive IIR Filtered-v Algorithms for ANC.J Acoust Soc Am 1997 101 4 2079-2103. 被引量:1

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