In a recent paper, we have proposed a novel approach for measuring the room impulse response (RIR) robust toward the nonlinearities affecting the power amplifier or the loudspeaker. The approach is implemented by modeling the acoustic path as a Legendre nonlinear (LN) filter and by measuring the first-order kernel using perfect periodic sequences (PPSs) and the cross-correlation method. PPSs are periodic sequences that guarantee the perfect orthogonality of the basis functions of a certain nonlinear filter over a period. For LN filters, PPSs have approximately a uniform distribution. We have shown that also the Wiener Nonlinear (WN) filters, which derive from the truncation of the Wiener series, admit PPSs, whose sample distribution approximates a Gaussian distribution. Thus, WN filters and their PPSs appear more appealing for measuring the RIR. The paper discusses RIR measurement using WN filters and PPSs and explains how PPSs for WN filter suitable for RIR identification can be developed. Experimental results, using signals affected by real nonlinear devices, illustrate the effectiveness of the proposed approach and compare it with that based on LN filters.

On room impulse response measurement using perfect sequences for Wiener nonlinear filters

Carini, Alberto;
2018

Abstract

In a recent paper, we have proposed a novel approach for measuring the room impulse response (RIR) robust toward the nonlinearities affecting the power amplifier or the loudspeaker. The approach is implemented by modeling the acoustic path as a Legendre nonlinear (LN) filter and by measuring the first-order kernel using perfect periodic sequences (PPSs) and the cross-correlation method. PPSs are periodic sequences that guarantee the perfect orthogonality of the basis functions of a certain nonlinear filter over a period. For LN filters, PPSs have approximately a uniform distribution. We have shown that also the Wiener Nonlinear (WN) filters, which derive from the truncation of the Wiener series, admit PPSs, whose sample distribution approximates a Gaussian distribution. Thus, WN filters and their PPSs appear more appealing for measuring the RIR. The paper discusses RIR measurement using WN filters and PPSs and explains how PPSs for WN filter suitable for RIR identification can be developed. Experimental results, using signals affected by real nonlinear devices, illustrate the effectiveness of the proposed approach and compare it with that based on LN filters.
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Utilizza questo identificativo per citare o creare un link a questo documento: https://hdl.handle.net/11576/2662499
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