Skip to main content
SpringerLink
Log in

Sliding Mode Algorithm for Online Learning in Analog Multilayer Feedforward Neural Networks

  • Conference paper
  • First Online:
Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003 (ICANN 2003, ICONIP 2003)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 2714))

Abstract

A new dynamical sliding mode control algorithm is proposed for robust adaptive learning in analog multilayer feedforward networks with a scalar output. These type neural structures are widely used for modeling, identification and control of nonlinear dynamical systems. The zero level set of the learning error variable is considered as a sliding surface in the space of network learning parameters. The convergence of the algorithm is established and conditions are given. Its effectiveness is shown when applied to on-line learning of nonmonotonic function using a two-layered feedforward neural network.

This is a preview of subscription content, log in via an institution to check access.

Access this chapter

Log in via an institution
Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 39.99
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 54.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Institutional subscriptions

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

References

  1. Efe M. O., Kaynak O.: Stabilizing and Robustifying the Learning Mechanisms of Artificial Neural Networks in Control Engineering Applications. Int. Journal of Intelligent Systems, 15(5) (2000) 365–388

    Article  MATH  Google Scholar 

  2. Sira-Ramirez H., Colina-Morles E.: A Sliding Mode Strategy for Adaptive Learning in Adalines. IEEE Trans. on Circuits and Systems–I: Fundamental Theory and Applications. 42(12) (1995) 1001–1012

    Article  Google Scholar 

  3. Yu X., Zhihong M., Rahman S. M. M.: Adaptive Sliding Mode Approach for Learning in a Feedforward Neural Network. Neural Computing & Applications. 7 (1998) 289–294

    Article  MATH  Google Scholar 

  4. Parma G. G., Menezes B. R., Braga A. P.: Sliding Mode Algorithm for Training Multilayer Artificial Neural Networks. Electronics Letters. 34(1) (1998) 97–98.

    Article  Google Scholar 

  5. G. G. Parma G. G., Menezes B. R., Braga A. P.: Neural Networks Learning with Sliding Mode Control: the Sliding Mode Backpropagation Algorithm. Int. Journal of Neural Systems. 9(3) (1999) 187–194

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. branch Plovdiv, Control Systems Department, Technical University Sofia, 25, Canko Dustabanov str., 4000, Plovdiv, Bulgaria

    Andon V.

  2. Bogazici University, 80815, Istanbul, Turkey

    Nikola G., Andon V. & Okyay Kaynak

Authors
  1. Nikola G.
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andon V.
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Okyay Kaynak
    View author publications

    You can also search for this author in PubMed Google Scholar

Editor information

Editors and Affiliations

  1. Bogazici University, Bebek, 34342, Istanbul, Turkey

    Okyay Kaynak  & Ethem Alpaydin  & 

  2. Laboratory of Computer and Information Science, Helsinki University of Technology, P.O.B. 5400, 02015, Finland

    Erkki Oja

  3. Department of Computer Science and Engineering, The Chinese University of Hong Kong, Shatin, Hong Kong

    Lei Xu

Rights and permissions

Reprints and permissions

Copyright information

© 2003 Springer-Verlag Berlin Heidelberg

About this paper

Cite this paper

G., N., V., A., Kaynak, O. (2003). Sliding Mode Algorithm for Online Learning in Analog Multilayer Feedforward Neural Networks. In: Kaynak, O., Alpaydin, E., Oja, E., Xu, L. (eds) Artificial Neural Networks and Neural Information Processing — ICANN/ICONIP 2003. ICANN ICONIP 2003 2003. Lecture Notes in Computer Science, vol 2714. Springer, Berlin, Heidelberg. https://doi.org/10.1007/3-540-44989-2_127

Download citation

  • DOI: https://doi.org/10.1007/3-540-44989-2_127

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-40408-8

  • Online ISBN: 978-3-540-44989-8

  • eBook Packages: Springer Book Archive

Publish with us

Policies and ethics

Search

Navigation