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Application of Common-Pole Parallel Filters to Nonlinear Models Based on Orthogonal Functions

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Different nonlinear models are exploited to model real-world devices. Among them, an effective technique is based on the combination of orthogonal nonlinear functions and frequency-domain adaptive filtering algorithms for nonlinear system identification. In this paper first the independence of the model from the orthogonal basis is demonstrated by complementing previously obtained results. Then, a highly efficient model implementation is presented by taking advantage of fixed pole parallel filters for the linear filtering part. The efficiency comes both from using common-pole modeling and from applying a warped filter design that takes into account the frequency resolution of human hearing. Experimental results prove the effectiveness of the proposed approach showing its suitability in real-time digital simulation of nonlinear audio devices.

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