Skip to main content
Log in

Artificial neural networks

A brief introduction

  • General Article
  • Published:
Resonance Aims and scope Submit manuscript

Abstract

Artificial neural networks are ‘biologically’ inspired networks. They have the ability to learn from empirical data/ information. They find use in computer science and control engineering fields.

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

Access this article

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Similar content being viewed by others

Suggested Reading

  • J M Zurada. Introduction to Artificial Neural Systems. West Publishing Company, New York. 1992.

    Google Scholar 

  • S Haykin. Neural Networks — A Comprehensive Foundation. IEEE, New York. 1994.

    Google Scholar 

  • B Kosko. Neural Networks and Fuzzy Systems — A Dynamical Systems Approach to Machine Intelligence. Prentice Hall, Englewood Cliffs, N.J. 1992.

    Google Scholar 

  • R C Eberhart and R W Dobbins. Neural Network PC Took — A Practical Guide. Academic Press Inc., New York. 1992.

    Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Rights and permissions

Reprints and permissions

About this article

Cite this article

Raol, J.R., Mankame, S.S. Artificial neural networks. Reson 1, 47–54 (1996). https://doi.org/10.1007/BF02835699

Download citation

  • Issue Date:

  • DOI: https://doi.org/10.1007/BF02835699

Keywords

Navigation