Abstract
The neural scheme for data association in multi-target environment is proposed. This scheme is derived by using the Lyapunov energy function and is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. Through the experiments, we show that the proposed scheme is stable and works well in general environments. © Springer-Verlag Berlin Heidelberg 2006.
Cite
CITATION STYLE
Lee, Y. W. (2006). Development of the Hopfield neural scheme for data association in multi-target tracking. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 3971 LNCS, pp. 1280–1285). Springer Verlag. https://doi.org/10.1007/11759966_190
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