The study of the robust learning algorithm for neural networks

  • Authors:

  • Shigenobu Yamawaki

  • Affiliations:

  • Department of Electric and Electronic Engineering, School of Science and Engineering, Kinki University, Osaka, Japan

  • Venue:
  • KES'06 Proceedings of the 10th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part II
  • Year:
  • 2006

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Abstract

In this paper, we propose the robust learning algorithm for neural networks. The suggested algorithm is obtaining the expanded Kalman filter in the Krein space. We show that this algorithm can be applied to identify the nonlinear system in the presence of the observed noise and system noise.