This paper presents a numerically stable fast Newton-type adaptive filter algorithm. Two problems are dealt with in the paper. First, we derive the proposed algorithm from an order-recursive least squares algorithm. T...
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This paper presents a numerically stable fast Newton-type adaptive filter algorithm. Two problems are dealt with in the paper. First, we derive the proposed algorithm from an order-recursive least squares algorithm. The result of the proposed algorithm is equivalent to that of the fast Newton transversal filter (FNTF) algorithm. However, the derivation process is different. Instead of extending a covariance matrix of the input based on the min-max and the max-min criteria, the derivation shown in this paper is to solve an optimum extension problem of the gain vector based on the information of the Mth-order forward or backward predictor. The derivation provides an intuitive explanation of the FNTF algorithm, which may be easier to understand. Second, we present stability analysis of the proposed algorithm using a linear time-variant state-space method. We show that the proposed algorithm has a well-analyzable stability structure, which is indicated by a transition matrix. The eigenvalues of the ensemble average of the transition matrix are proved all to be asymptotically less than unity. This results in a much-improved numerical performance of the proposed algorithm compared with the combination of the stabilized fast recursive least squares (SFRLS) and the FNTF algorithms. Computer simulations implemented by using a finite-precision arithmetic have confirmed the validity of our analysis.
In order to control the noise of the heavy truck interior cab effectively, the active noise control methods are employed. First, an interior noise field test for the heavy truck is performed, and frequencies of interi...
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In order to control the noise of the heavy truck interior cab effectively, the active noise control methods are employed. First, an interior noise field test for the heavy truck is performed, and frequencies of interior noise of this vehicle are analyzed. According to the spectrum analysis of acquired noise signal, it is found out that the main frequencies of interior noise are less than 800Hz. Then the least squares lattice （lsl） algorithm is used as signal processing algorithm of the controller and a closed-loop control DSP system, based on TMS 320VC5416, is developed. The residual signal at driver＇s ear is used as feedback signal. Lastly, the developed ANC system is loaded into the heavy truck cab, and controlling the noise at driver＇ s ear for that truck at different driving speeds is attempted. The noise control test results indicate that the cab interior noise is reduced averagely by 0.9 dBA at different driving speeds.
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