Parallel Approach to the Levenberg-Marquardt Learning Algorithm for Feedforward Neural Networks

  • Jarosław Bilski
  • Jacek Smoląg
  • Jacek M. Żurada
Conference paper

DOI: 10.1007/978-3-319-19324-3_1

Part of the Lecture Notes in Computer Science book series (LNCS, volume 9119)
Cite this paper as:
Bilski J., Smoląg J., Żurada J.M. (2015) Parallel Approach to the Levenberg-Marquardt Learning Algorithm for Feedforward Neural Networks. In: Rutkowski L., Korytkowski M., Scherer R., Tadeusiewicz R., Zadeh L., Zurada J. (eds) Artificial Intelligence and Soft Computing. ICAISC 2015. Lecture Notes in Computer Science, vol 9119. Springer, Cham

Abstract

A parallel architecture of the Levenberg-Marquardt algorithm for training a feedforward neural network is presented. The proposed solution is based on completely new parallel structures to effectively reduce high computational load of this algorithm. Detailed parallel neural network structures are explicitely discussed.

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Copyright information

© Springer International Publishing Switzerland 2015

Authors and Affiliations

  • Jarosław Bilski
    • 1
  • Jacek Smoląg
    • 1
  • Jacek M. Żurada
    • 2
    • 3
  1. 1.Institute of Computational IntelligenceCzȩstochowa University of TechnologyCzȩstochowaPoland
  2. 2.Information Technology InstituteUniversity of Sociel SciencesŁódźPoland
  3. 3.Department Electrical and Computer EngineeringUniversity of LouisvilleLouisvilleUSA

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