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Lyapunov stability-Dynamic Back Propagation-based comparative study of different types of functional link neural networks for the identification of nonlinear systems

  • Rajesh KumarEmail author
  • Smriti Srivastava
  • Amit Mohindru
Methodologies and Application
  • 6 Downloads

Abstract

In this paper, the performance comparison of various types of functional link neural networks (FLNNs) has been done for the nonlinear system identification. The FLNNs being compared in the present study are: trigonometry FLNN, Legendre FLNN (LeFLNN), Chebyshev FLNN, power series FLNN (PSFLNN) and Hermite FLNN. The recursive weights adjustment equations are derived using the combination of Lyapunov stability criterion and dynamic back propagation algorithm. In the simulation study, a total of three nonlinear systems (both static and dynamic systems) are considered for testing and comparing the approximation ability and computational complexity of the above-mentioned FLNNs. From the simulation results, it is observed that the LeFLNN has given better approximation accuracy and PSFLNN offered least computational load as compared to the rest models.

Keywords

Functional link neural network Nonlinear systems Dynamic back propagation algorithm Identification Lyapunov stability analysis Adaptive learning rate 

Notes

Acknowledgements

This study is not funded by any agency.

Compliance with ethical standards

Conflict of interest

The authors declare that they have no conflict of interest.

Human and animal rights

This article does not contain any studies with human participants or animals performed by any of the authors.

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Copyright information

© Springer-Verlag GmbH Germany, part of Springer Nature 2019

Authors and Affiliations

  1. 1.Department of Electrical and Instrumentation EngineeringThapar Institute of Engineering and Technology (Deemed to be University)PatialaIndia
  2. 2.Division of Instrumentation and Control EngineeringNetaji Subhas University of Technology (formerly Netaji Subhas Institute of Technology)New DelhiIndia
  3. 3.Department of Electronics and Communication EngineeringIndraprastha Institute of Information TechnologyNew DelhiIndia

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