Back-propagation algorithm based on the extended Kalman filter

Aritoshi Kimura, Ikuo Arizono, Hiroshi Ohta

Research output: Chapter in Book/Report/Conference proceedingConference contribution

1 Citation (Scopus)

Abstract

Recently, Watanabe et al. proposed a back-propagation algorithm, in which the learning rate is time-varying, based on the extended Kalman filter (EKF). In the algorithm the interconnection strengths and biases are treated as the independent variables. However, the interconnection strengths and biases are not always independent, and have generally the mutual correlations. In this paper, we propose a new back-propagation algorithm in the case of considering the mutual correlations between the interconnection strengths and biases. Furthermore, by applying the proposed learning algorithm to the XOR problem and comparing with the algorithm of Watanabe et al., the ability of the proposed learning algorithm is examined.

Original languageEnglish
Title of host publicationProceedings of the International Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Pages1669-1672
Number of pages4
Volume2
ISBN (Print)0780314212
Publication statusPublished - 1993
Externally publishedYes
EventProceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3) - Nagoya, Jpn
Duration: Oct 25 1993Oct 29 1993

Other

OtherProceedings of 1993 International Joint Conference on Neural Networks. Part 2 (of 3)
CityNagoya, Jpn
Period10/25/9310/29/93

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ASJC Scopus subject areas

  • Software

Cite this

Kimura, A., Arizono, I., & Ohta, H. (1993). Back-propagation algorithm based on the extended Kalman filter. In Anon (Ed.), Proceedings of the International Joint Conference on Neural Networks (Vol. 2, pp. 1669-1672). Publ by IEEE.