Eigenvalue equalization filtered-x algorithm for the multichannel active noise control of stationary and nonstationary signals

The FXLMS algorithm, which is extensively used in active noise control, exhibits frequency dependent convergence behavior. This leads to degraded performance for time-varying and multiple frequency signals. A new algorithm called the eigenvalue equalization filtered-x least mean squares (EE-FXLMS) has been developed to overcome this limitation without increasing the computational burden of the controller. The algorithm is easily implemented for either single or multichannel control. The magnitude coefficients of the secondary path transfer function estimate are altered while preserving the phase. For a reference signal that has the same magnitude at all frequencies, the secondary path estimate is given a flat response over frequency. For a reference signal that contains tonal components of unequal magnitudes, the magnitude coefficients of the secondary path are adjusted to be the inverse magnitude of the reference tones. Both modifications reduce the variation in the eigenvalues of the filtered-x autocorrelation matrix and lead to increased performance. Experimental results show that the EE-FXLMS algorithm provides 3.5-4.4 dB additional attenuation at the error sensor compared to normal FXLMS control. The EE-FXLMS algorithm's convergence rate at individual frequencies is faster and more uniform than the normal FXLMS algorithm with several second improvement being seen in some cases.