Compared to finite impulse response (FIR) filters, infinite impulse response (IIR) filters can match the system better with much fewer coefficients, and hence the computation load is saved and the performance improves...Compared to finite impulse response (FIR) filters, infinite impulse response (IIR) filters can match the system better with much fewer coefficients, and hence the computation load is saved and the performance improves. Therefore, it is attractive to use IIR filters instead of FIR filters in active noise control (ANC). However, filtered-U LMS (FULMS) algorithm, the IIR filter-based algorithm commonly used so far cannot ensure global convergence. A new IIR filter based adaptive algorithm, which can ensure global convergence with computation load only slightly increasing, is proposed in this paper. The new algorithm is called as filtered-e LMS algorithm since the error signal of which need to be filtered. Simulation results show that the FELMS algorithm presents better performance than the FULMS algorithm.展开更多
基金This work was supported by the National High Technology Research and Development of China(863 Program:2002AA412410).
文摘Compared to finite impulse response (FIR) filters, infinite impulse response (IIR) filters can match the system better with much fewer coefficients, and hence the computation load is saved and the performance improves. Therefore, it is attractive to use IIR filters instead of FIR filters in active noise control (ANC). However, filtered-U LMS (FULMS) algorithm, the IIR filter-based algorithm commonly used so far cannot ensure global convergence. A new IIR filter based adaptive algorithm, which can ensure global convergence with computation load only slightly increasing, is proposed in this paper. The new algorithm is called as filtered-e LMS algorithm since the error signal of which need to be filtered. Simulation results show that the FELMS algorithm presents better performance than the FULMS algorithm.
