This paper firstly introduces an extended plant adaptive neural network model which can be on-line adapted conveniently, then presents a method of active noise control using adaptive neural networks.
本文首先引入一个能方便进行在线自适应的扩展控制对象自适应神经网络模型，在此基础上提出一种噪声有源控制的自适应神经网络方法。
It is very important to model the secondary paths in adaptive active noise control algorithms.
误差通道建模是实现自适应有源噪声控制算法的重要环节。
So an active noise cancellation (anc) system for helicopter cabin noise based on adaptive internal model control technique, is developed in laboratory.
从而在实验室构造了一套基于自适应内模控制技术的主动消声系统(anc)。
An active noise self-tuning model predictive control approach is derived. An on-line learning algorithm is proposed for adjusting the uncertain model parameters.
将预测控制方法应用到有源噪声控制领域，给出了一种参数在线自适应算法，该算法的收敛速度不受次级声路径响应的影响。
An active noise self-tuning model predictive control approach is derived. An on-line learning algorithm is proposed for adjusting the uncertain model parameters.
将预测控制方法应用到有源噪声控制领域，给出了一种参数在线自适应算法，该算法的收敛速度不受次级声路径响应的影响。
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