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Identification of Linear Systems with Nonlinear Distortions
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TLDR
A theoretical framework is proposed that extends the linear system description to include the impact of nonlinear distortions: the nonlinear system is replaced by a linear model plus a 'nonlinear noise source'.Abstract:
This paper studies the impact of nonlinear distortions on linear system identification. It collects a number of previously published methods in a fully integrated approach to measure and model these systems from experimental data. First a theoretical framework is proposed that extends the linear system description to include the impact of nonlinear distortions: the nonlinear system is replaced by a linear model plus a 'nonlinear noise source'. The class of nonlinear systems covered by this approach is described and the properties of the extended linear representation are studied. These results are used to design the experiments; to detect the level of the nonlinear distortions; to measure efficiently the 'best' linear approximation; to reveal the even or odd nature of the nonlinearity; to identify a parametric linear model; and to improve the model selection procedures in the presence of nonlinear distortions.read more
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References
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Laurent Vanbeylen,A. Van Mulders +1 more
TL;DR: In this paper, a black-box nonlinear LFR (Linear Fractional Representation) model consisting of MIMO linear dynamics and a SISO static nonlinear part is presented.
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TL;DR: In this paper, a simple automatic method to suppress system transients and unmodelled dynamics during variance analysis is proposed, without the need of separate observation noise analysis or of full-blown nonlinear analysis.
Large-SignalAnalysis Including the Baseband
Guillaume Pailloncy,Gustavo Avolio,Maciej Tomasz Myslinski,Yves Rolain,Marc Vanden Bossche,D. Schreurs +5 more
Proceedings ArticleDOI
Structural and Functional Changes Occuring During Growth of the Respiratory System Can Be Quantified and Classified
TL;DR: The results obtained suggest that the proposed device, method and index are a successful combination of lung function testing, signal processing and classification items.