Title :
Feedforward adaptive noise control with multivariable gradient lattice filters
Author :
Chen, S.-J. ; Gibson, James Steven
Author_Institution :
Dept. of Mech. Eng., Nat. Central Univ., Chung-Li, Taiwan
fDate :
3/1/2001 12:00:00 AM
Abstract :
This work presents a novel feedforward adaptive noise control (ANC) algorithm based on multivariable gradient lattice filters to control acoustic noise or vibration globally. In addition, a gradient-based lattice for AR and FIR models and its transpose lattice for the multivariable ANC algorithm are derived. The filter has different forward and backward reflection coefficient matrices to provide a faster convergence than the gradient lattice algorithm when using the same reflection coefficient matrices. Experimental results demonstrate the effectiveness of the proposed algorithm in controlling broadband acoustic noise in an enclosure
Keywords :
FIR filters; acoustic signal processing; adaptive filters; adaptive signal processing; autoregressive processes; convergence of numerical methods; feedforward; filtering theory; lattice filters; matrix algebra; multivariable systems; noise abatement; vibration control; AR model; FIR model; acoustic noise control; adaptive filtering; backward reflection coefficient matrix; broadband acoustic noise control; convergence; enclosure; feedforward adaptive noise control; forward reflection coefficient matrix; gradient lattice algorithm; multivariable ANC algorithm; multivariable gradient lattice filters; transpose lattice; vibration control; Acoustic noise; Adaptive control; Adaptive filters; Finite impulse response filter; Lattices; Noise cancellation; Programmable control; Resonance light scattering; Signal processing algorithms; Transversal filters;
Journal_Title :
Signal Processing, IEEE Transactions on
