A periodic sequence is defined as a perfect periodic sequence for a certain nonlinear filter if the cross-correlation between any two of the filter basis functions, estimated over a period, is zero. Using a perfect periodic sequence as input signal, an unknown nonlinear system can be efficiently identified with the cross-correlation method. Moreover, the basis functions that guarantee the most compact representation according to some information criterion can also be easily estimated. Perfect periodic sequences have already been developed for even mirror Fourier, Legendre and Chebyshev nonlinear filters. In this paper, we show they can be developed also for nonlinear Wiener filters. Their development is non-trivial and differs from that of the other nonlinear filters, since Wiener filters have orthogonal basis functions for white Gaussian input signals. Experimental results highlight the usefulness of the proposed perfect periodic sequences in comparison with the Gaussian input signals commonly used for Wiener filter identification
An adaptive multichannel and multiple position room response equalization system is proposed. The room responses are adaptively estimated with good accuracy by reducing the interchannel coherence with a technique based on the missing fundamental phenomenon, that introduces only a mild alteration of the sound timbre. The equalizer is designed in warp frequency domain for improving equalization in the low frequency region, reducing the computational cost of the design and deriving an algorithm capable to work in real time. Simulation results using signals acquired in a real environment illustrate the effectiveness of the proposed approach.
The paper proposes a novel approach for measuring the room impulse response that is robust toward the nonlinearities affecting the power amplifier or the loudspeaker. The approach is implemented by modeling the acoustic path as a Legendre nonlinear filter and by measuring the first-order kernel using perfect periodic sequences and the cross-correlation method. Perfect sequences for Legendre filters are periodic sequences that guarantee the orthogonality of the Legendre basis functions over a period. They ensure the robustness of the first kernel measurement toward nonlinear distortions. The paper also explains how perfect periodic sequences for Legendre filters that are suitable for room impulse response identification can be developed. Experimental results involving both simulated and real environments illustrate the effectiveness and the robustness of the proposed approach
Nonlinear models are exploited in the field of digital audio systems for modelling most of real-world devices that show a nonlinear behaviour. Among nonlinear models, Hammerstein systems are realized through a static nonlinearity cascaded with a linear filter. In this paper, the Hammerstein coefficients are estimated using an adaptive Catmull-Rom cubic spline for the static nonlinearity and an adaptive FIR filter for the dynamic linear system also introducing a pre-processing for the time delay estimation. Experimental results confirm the effectiveness of the proposed approach, making also comparisons with existing techniques of the state of the art.
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