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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.

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Citations
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Proceedings ArticleDOI

A Pruning Technique for Volterra Models: Exploiting Knowledge About Input Spectrum

TL;DR: The purpose of this work is presenting a method to reduce the number of coefficients defining the Volterra models by exploiting a priori knowledge about the input signal spectral content and results clearly show the advantages with respect to a conventional polynomial model.
Book ChapterDOI

Measuring and Analysing Nonlinearities in the Lung Tissue

TL;DR: The results indicate that the proposed method and index are useful for clinical classification of viscoelastic properties in the lungs.
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Non-linear Effects in the Respiratory Impedance

TL;DR: The link between the non-linear distortions and the lumped fractional order model parameters is introduced, thus completing the puzzle of this book.

Initial Estimates forWiener-Hammerstein Models using theBestLinear Approximation

TL;DR: In this article, the authors proposed a method to initialize the linear dynamic blocks of a Wiener-Hammerstein model using a linear-in-the-parameters (LINP) problem.
Journal ArticleDOI

Magnitude-only modeling for sigma-delta modulator characterization

TL;DR: A new magnitude-only transfer-function modeling framework for SDM architectures, which is based on output noise spectrum and produces a stable LTI NTF approximation model, based on a phase reconstruction and a rational transfer- function fitting step, using the Vector Fitting algorithm.
References
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Journal ArticleDOI

A new look at the statistical model identification

TL;DR: In this article, a new estimate minimum information theoretical criterion estimate (MAICE) is introduced for the purpose of statistical identification, which is free from the ambiguities inherent in the application of conventional hypothesis testing procedure.
Book

System Identification: Theory for the User

Lennart Ljung
TL;DR: Das Buch behandelt die Systemidentifizierung in dem theoretischen Bereich, der direkte Auswirkungen auf Verstaendnis and praktische Anwendung der verschiedenen Verfahren zur IdentifIZierung hat.
Journal ArticleDOI

Paper: Modeling by shortest data description

Jorma Rissanen
- 01 Sep 1978 - 
TL;DR: The number of digits it takes to write down an observed sequence x1,...,xN of a time series depends on the model with its parameters that one assumes to have generated the observed data.
Book

Engineering Applications of Correlation and Spectral Analysis

TL;DR: This chapter discusses single-Input/Single-Output Relationships, nonstationary data analysis techniques, and procedures to Solve Multiple- Input/Multiple-Output Problems.
Journal ArticleDOI

Nonlinear black-box modeling in system identification: a unified overview

TL;DR: What are the common features in the different approaches, the choices that have to be made and what considerations are relevant for a successful system-identification application of these techniques are described, from a user's perspective.
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