Abstract
The broadband Kalman filter (BKF) and general Kalman filter (GKF) have been proposed for the application of acoustic system identification. Here, the authors present a multiband-structured Kalman filter (MSKF) to speed up the convergence rate of BKF and GKF for highly correlated signal. A simplified version of MSKF (SMSKF) is also provided at the aim of reducing the complexity. It is shown that the BKF and GKF are the special cases of the proposed MSKF, and the SMSKF can be treated as the improved multiband-structured subband adaptive filter algorithm with a variable regularisation matrix. The low-complexity implementation of SMSKF, both in the fast filtering and matrix inversion operation, is discussed. Computer simulations confirm the performance advantage of the proposed algorithm.
Published Version
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