A TRANSFORM DOMAIN OPTIMIZATION TO INCREASE THE CONVERGENCE SPEED OF THE MULTICHANNEL FILTERED-X LEAST-MEAN-SQUARE ALGORITHM

The main drawback of the multichannel filtered-X LMS (FX-LMS) algorith m for the active noise control (ANC) of broadband disturbances is its low convergence speed when the filtered reference signals are strongly correlated, producing a large eigenvalue spread in the global correla tion matrix, This correlation can be caused either by autocorrelation of the signals of the reference sensors, or by coupling between the '' error paths'' which introduces intercorrelation in the filtered refere nce signals. Multichannel versions of fast convergence monochannel alg orithms exist (Newton-LMS, RLS, fast Kalman), but these algorithms eit her require too many computations for practical implementations, or th ey require the optimization of the controller to be performed at each sample, which can be a serious constraint. The purpose of this paper i s to introduce a multichannel algorithm that has a high convergence sp eed and a low computational load, close to the FX-LMS. It is called th e cosine transform filtered-X LMS (CTFX-LMS) because it uses a discret e cosine transform to eliminate the correlation that slows down the co nvergence process. The fundamental differences between this algorithm and many previously published frequency domain algorithms will be expl ained, Results of active noise control experiments in ducts will valid ate the convergence behavior of the new algorithm. (C) 1996 Acoustical Society of America.