Estimation-based multi-channel adaptive algorithm for filtered-LMS problems

Presents an estimation-based adaptive filtering algorithm for the multi-channel filtered-LMS problems where a number of adaptively controlled secondary sources use multiple reference signals to cancel the effect of a number of primary sources (i.e. disturbance sources) as seen by a number of error sensors. We show that our estimation based approach easily extends to the multi-channel case, and that it maintains all of the stability and performance features of the single-channel solution. The problem of noise cancellation in a one dimensional acoustic duct, and a structural vibration control problem are chosen to examine the main characteristics of the proposed multi-channel adaptive algorithm. The performance of the new multi-channel adaptive algorithm is compared to the performance of a multi-channel implementation of the FxLMS algorithm in these cases, and it is shown that the new algorithm provides a faster response, with improved transient behavior and steady-state performance.