Nonlinear system identification using modified variational autoencoders

Nonlinear system identification using modified variational autoencoders

This research proposes a methodology for identifying nonlinear systems using input/output data and deep learning generative models. Our framework integrates Variational Autoencoders (VAE) with Nonlinear Autoregressive with exogenous input (NARX) in a unified identification structure to address overf...

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Bibliographic Details
Main Authors: Jose L. Paniagua, Jesús A. López
Format: Article
Language:English
Published: Elsevier 2024-06-01
Series:Intelligent Systems with Applications
Subjects:
System identification
Deep learning
Generative modeling
Nonlinear dynamic systems
Online Access:http://www.sciencedirect.com/science/article/pii/S2667305324000206

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http://www.sciencedirect.com/science/article/pii/S2667305324000206

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