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access icon free Active impulsive noise control algorithm with post adaptive filter coefficient filtering

© The Institution of Engineering and Technology
Received 31/05/2012, Accepted 04/03/2013, Revised 21/11/2012, Published

Most algorithms for active impulsive noise control employ non-linear transformations to limit the reference and/or error signals and to maintain system stability. From a more direct manner, a new cost function is proposed in this study which is defined as the summation of the squared Euclidean norm of difference between the currently updated filter coefficients vector and all past filter coefficients vector subject to the constraint imposed on the adaptive filter output. A new adaptive algorithm is derived from the cost function and called the filtered weight filtered-x normalised least mean square algorithm because it can be interpreted as a post filter structure which passes the filter coefficients through a first-order infinite impulse response filter. The proposed algorithm is suitable for active control of impulsive noise since it directly limits the dynamic range of the adaptive filter coefficients and prevents heavy fluctuation of the filter coefficients. Simulations compare the performance of the proposed algorithm with the existing algorithms and demonstrate the effectiveness of the proposed algorithm.

Inspec keywords: transforms; least mean squares methods; IIR filters; adaptive filters; active noise control

Other keywords: nonlinear transformations; dynamic range; filtered weight filtered-x normalised least mean square algorithm; filter coefficients vector; system stability; IIR filter; cost function; first-order infinite impulse response filter; error signals; squared Euclidean norm; post adaptive filter coefficient filtering; active impulsive noise control algorithm

Subjects: Other nonelectric variables control; Integral transforms in numerical analysis; Interpolation and function approximation (numerical analysis); Filtering methods in signal processing; Interpolation and function approximation (numerical analysis); Integral transforms in numerical analysis

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