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A Study on the Hopfield Neural Scheme for Data Association in Multi­Target Tracking  

Lee, Yang­-Weon (호남대학교 정보통신공학과)
Publication Information
Journal of the Korea Institute of Information and Communication Engineering / v.7, no.8, 2003 , pp. 1840-1847 More about this Journal
Abstract
In this paper, we have developed the MHDA scheme for data association. This scheme is important in providing a computationally feasible alternative to complete enumeration of JPDA which is intractable. We have proved that given an artificial measurement and track's configuration, MHDA scheme converges to a proper plot in a finite number of iterations. Also, a proper plot which is not the global solution can be corrected by re­initializing one or more times. In this light, even if the performance is enhanced by using the MHDA, we also note that the difficulty in tuning the parameters of the MHDA is critical aspect of this scheme. The difficulty cat however, be overcome by developing suitable automatic instruments that will iteratively verify convergence as the network parameters vary.
Keywords
Neural Network; Hopfield; Multi­target tracking; Data association;
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