Learning temporal sequences by complex neurons with local feedback

Makoto Kinouchi, Masafumi Hagiwara

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

9 Citations (Scopus)

Abstract

To deal with temporal sequences is very important and difficult problem for applications of neural networks. In this paper, we propose a Multilayer Network using Complex neurons with local Feedback (MNCF). A complex neuron can keep previous information by the phase component. We derive simple learning algorithm based on the back-propagation for temporal sequences. It is shown in computer simulations that the proposed network has better ability than the conventional real ones, including Elman's network.

Original languageEnglish
Title of host publicationIEEE International Conference on Neural Networks - Conference Proceedings
PublisherIEEE
Pages3165-3169
Number of pages5
Volume6
Publication statusPublished - 1995
EventProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6) - Perth, Aust
Duration: 1995 Nov 271995 Dec 1

Other

OtherProceedings of the 1995 IEEE International Conference on Neural Networks. Part 1 (of 6)
CityPerth, Aust
Period95/11/2795/12/1

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ASJC Scopus subject areas

  • Software

Cite this

Kinouchi, M., & Hagiwara, M. (1995). Learning temporal sequences by complex neurons with local feedback. In IEEE International Conference on Neural Networks - Conference Proceedings (Vol. 6, pp. 3165-3169). IEEE.