Quantitative object motion prediction by an adaptive resonance theory (ART) neural network

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

Abstract

An Adaptive Resonance Theory (ART) neural network is applied for the estimation and prediction of object motion states in real time. A bottom-up process of the network keeps track of the motion history of the object and a topdown process generates the prediction of the object motion. A retrospective enforcement process adjusts the network parameters to respond dynamically to the object motion. The process does not require any assumption of the object motion model and is applicable to a variety of situations where object motion exhibits irregular and abrupt variations.

Original languageEnglish (US)
Title of host publicationProceedings of the American Control Conference
PublisherPubl by American Automatic Control Council
Pages41-45
Number of pages5
ISBN (Print)0780302109
StatePublished - Dec 1 1992
EventProceedings of the 1992 American Control Conference - Chicago, IL, USA
Duration: Jun 24 1992Jun 26 1992

Publication series

NameProceedings of the American Control Conference
Volume1
ISSN (Print)0743-1619

Other

OtherProceedings of the 1992 American Control Conference
CityChicago, IL, USA
Period6/24/926/26/92

Fingerprint

Neural networks

ASJC Scopus subject areas

  • Control and Systems Engineering

Cite this

Zhu, Q. (1992). Quantitative object motion prediction by an adaptive resonance theory (ART) neural network. In Proceedings of the American Control Conference (pp. 41-45). (Proceedings of the American Control Conference; Vol. 1). Publ by American Automatic Control Council.

Quantitative object motion prediction by an adaptive resonance theory (ART) neural network. / Zhu, Qiuming.

Proceedings of the American Control Conference. Publ by American Automatic Control Council, 1992. p. 41-45 (Proceedings of the American Control Conference; Vol. 1).

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

Zhu, Q 1992, Quantitative object motion prediction by an adaptive resonance theory (ART) neural network. in Proceedings of the American Control Conference. Proceedings of the American Control Conference, vol. 1, Publ by American Automatic Control Council, pp. 41-45, Proceedings of the 1992 American Control Conference, Chicago, IL, USA, 6/24/92.
Zhu Q. Quantitative object motion prediction by an adaptive resonance theory (ART) neural network. In Proceedings of the American Control Conference. Publ by American Automatic Control Council. 1992. p. 41-45. (Proceedings of the American Control Conference).
Zhu, Qiuming. / Quantitative object motion prediction by an adaptive resonance theory (ART) neural network. Proceedings of the American Control Conference. Publ by American Automatic Control Council, 1992. pp. 41-45 (Proceedings of the American Control Conference).
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