Quantitative object motion prediction by an ART2 and Madaline combined neural network: Concepts and experiments

Authors

Qiuming Zhu, University of Nebraska at OmahaFollow
Ahmed Y. Tawfik, University of Nebraska at Omaha

Document Type

Article

Publication Date

1-1995

Publication Title

Journal of Neural Processing Letters

Volume

2

Issue

1

First Page

19

Last Page

21

Abstract

An ART2 and a Madaline combined neural network is applied to predicting object motions in dynamic environments. The ART2 network extracts a set of coherent patterns of the object motion by its self-organizing and unsupervised learning features. The identified patterns are directed to the Madaline network to generate a quantitative prediction of the future motion states. The method does not require any presumption of the mathematical models, and is applicable to a variety of situations.

Comments

The final publication is available at Springer via http://link.springer.com/article/10.1007/BF02312378.

Recommended Citation

Zhu, Qiuming and Tawfik, Ahmed Y., "Quantitative object motion prediction by an ART2 and Madaline combined neural network: Concepts and experiments" (1995). Computer Science Faculty Publications. 36.
https://digitalcommons.unomaha.edu/compscifacpub/36