Deep inference: A convolutional neural networks method for parameter recovery of the fractional dynamics

Document Type : Research Paper

Authors

1 Faculty of Sciences, Imam Ali University, Tehran, Iran

2 Department of Cognitive Modeling, Institute for Cognitive and Brain Sciences, Shahid Beheshti University, Tehran, Iran

3 Faculty of Engineering, Imam Ali University, Tehran Iran

Abstract

Parameter recovery of dynamical systems has attracted much attention in recent years. The proposed methods for this purpose can not be used in real-time applications. Besides, little works have been done on the parameter recovery of the fractional dynamics. Therefore, in this paper, a convolutional neural network is proposed for parameter recovery of the fractional dynamics. The presented network can also estimate the uncertainty of the parameter estimation and has perfect robustness for real-time applications.

Keywords

International Journal of Nonlinear Analysis and Applications
Volume 12, Issue 1
Winter and Spring 2021
Pages 189-201

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