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Adaptive Identification of Nonlinear Models Using Orthogonal Nonlinear Functions
System identification plays an important role in the field of digital audio systems. While the linear con- volution operation is suitable for linear systems, nonlinear models have to be introduced for modeling the majority of real-world devices. In this paper, a novel approach for the estimation of nonlinear system mod- els is proposed based on the introduction of suitable orthogonal nonlinear functions and frequency-domain adaptive filtering algorithm. Experimental results confirm the effectiveness of the approach, making also comparisons with an analogous approach based on a polynomial structure.
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