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Homophase signals separation for Volterra series identification

Damien Bouvier 1 Thomas Hélie 1 David Roze 1
1 S3AM - Systèmes et Signaux Sonores : Audio/Acoustique, instruMents
STMS - Sciences et Technologies de la Musique et du Son
Abstract : 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.
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Submitted on : Thursday, November 22, 2018 - 10:59:55 AM
Last modification on : Thursday, November 7, 2019 - 3:00:07 PM
Long-term archiving on: : Saturday, February 23, 2019 - 2:00:49 PM


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  • HAL Id : hal-01930662, version 1


Damien Bouvier, Thomas Hélie, David Roze. Homophase signals separation for Volterra series identification. 57th IEEE Conference on Decision and Control (CDC 2018), Dec 2018, Miami Beach, FL, United States. ⟨hal-01930662⟩



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