Multiple references active noise control with adaptive pruning
The active control algorithm for multiple reference signals is one of the research hotspots in the control of environmental noise with multiple noise sources.This paper designs a Sigmoid weighted filtered-x least mean square algorithm,which does not need to calculate the correlation between the reference signal and the error signal in advance for the selection of the reference signals.Self adjusting parameters are introduced into the reference signal to reduce the impact of irrelevant signals on the system.The comparison of simulation experiments has verified two advantages of the algorithm:firstly,the algorithm can be seen as adopting a variable step size strategy for each reference signal,and secondly,the algorithm can adjust the weights of the reference signals based on the correlation between the reference signal and the error signal,thus achieves adaptive pruning of the reference signals to reduce system overhead.
Active noise controlFiltered-x LMS algorithmCar noiseMultiple reference signals
万方数据
维普
