Volterra filters can be applied to a wide range of nonlinear systems, keeping only the low order kernels to yield a good approximation. The parametric array loudspeaker (PAL), as a weak nonlinear acoustic system, is a...
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Volterra filters can be applied to a wide range of nonlinear systems, keeping only the low order kernels to yield a good approximation. The parametric array loudspeaker (PAL), as a weak nonlinear acoustic system, is a...
详细信息
ISBN:
(纸本)9781467369985
Volterra filters can be applied to a wide range of nonlinear systems, keeping only the low order kernels to yield a good approximation. The parametric array loudspeaker (PAL), as a weak nonlinear acoustic system, is an attractive directional sound reproduction device. Volterra filters have been adopted in the linearization system of the PAL that efficiently reduces the nonlinear distortion with no need of solving the nonlinear acoustic equation. In this paper, the ultrasound-to-ultrasound Volterra filter is proposed, being inspired by the nonlinear acoustic principle, to provide a better systematic representation of the PAL. Experiment results are presented to prove the effectiveness of the proposed approach, where the sparse nlms algorithm is carried out in the identification.
This paper introduces a modified normalized least-mean-square (nlms) algorithm for sparse system identification. The proposed approach is in line with the proportionate nlms (Pnlms)-type algorithms in the sense that d...
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This paper introduces a modified normalized least-mean-square (nlms) algorithm for sparse system identification. The proposed approach is in line with the proportionate nlms (Pnlms)-type algorithms in the sense that different gains are considered in the coefficient update equation. However, in contrast to the Pnlms-type algorithms, the proposed approach considers only two different gains, one related to the active coefficients and other related to the inactive ones. Such an approach allows obtaining closed form expressions for both gains without relying on proportionality functions and activation factors. As a result of the proposed strategy, the new algorithm, termed here two-gain nlms (TG-nlms), leads to both fast convergence and low computational complexity. Simulation results are shown aiming to confirm the effectiveness of the proposed algorithm.
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