Feed-forward neural network with adaptive buffer length

Akihiro Tsunoda, Masafumi Hagiwara, Masao Nakagawa

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

Abstract

Summary form only given, as follows. A feedforward neural network with adaptive buffer length (FAB) was proposed and simulated. FAB has some buffers that store the past inputs and switches between the buffers and hidden units, which control the output of the buffers. Computer simulation results indicate that FAB can adjust the length of buffers for each input pattern automatically. FAB can also find the Markov dimension of the input sequences more effectively than the conventional dynamic network models.

Original languageEnglish
Title of host publicationProceedings. IJCNN - International Joint Conference on Neural Networks
Editors Anon
PublisherPubl by IEEE
Number of pages1
ISBN (Print)0780301641
Publication statusPublished - 1992 Jan 1
Externally publishedYes
EventInternational Joint Conference on Neural Networks - IJCNN-91-Seattle - Seattle, WA, USA
Duration: 1991 Jul 81991 Jul 12

Publication series

NameProceedings. IJCNN - International Joint Conference on Neural Networks

Other

OtherInternational Joint Conference on Neural Networks - IJCNN-91-Seattle
CitySeattle, WA, USA
Period91/7/891/7/12

ASJC Scopus subject areas

  • Engineering(all)

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  • Cite this

    Tsunoda, A., Hagiwara, M., & Nakagawa, M. (1992). Feed-forward neural network with adaptive buffer length. In Anon (Ed.), Proceedings. IJCNN - International Joint Conference on Neural Networks (Proceedings. IJCNN - International Joint Conference on Neural Networks). Publ by IEEE.