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Publication . Conference object . 2018

Homophase signals separation for Volterra series identification

Damien Bouvier; Thomas Hélie; David Roze;
Open Access
English
Published: 17 Dec 2018
Publisher: HAL CCSD
Country: France
Abstract
International audience; This article addresses the identification of non-linear systems represented by Volterra series. To improve the robustness of state-of-the-art estimation methods, we introduce the notion of "homophase signals", for which a separation method is given. Those homophase signals are then used to derive a robust identification process. This prior step is similar to nonlinear homogeneous order separation, in which amplitude relations are used to separate the orders of a Volterra series, but offers a better conditioning by using phase deviations rather than amplitudes. First an academic phase-based method using complex-valued test signals is introduced for separating nonlinear orders. Second this notion of phase deviation is extended to real-valued signals, which leads to the design of the proposed homophase signals separation method. Finally, a new identification process is derived using the homophase signals. Simulations are used to highlight the benefits of the proposed identification process in comparison to the standard approach.
Subjects by Vocabulary

Microsoft Academic Graph classification: Algorithm Phase deviation Nonlinear system Computer science Volterra series Separation method Amplitude Robustness (computer science) Homogeneous Estimation methods

Subjects

[SPI.SIGNAL]Engineering Sciences [physics]/Signal and Image processing, [PHYS.MECA.ACOU]Physics [physics]/Mechanics [physics]/Acoustics [physics.class-ph], [PHYS.MECA.VIBR]Physics [physics]/Mechanics [physics]/Vibrations [physics.class-ph]

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