Target motion prediction and tracking by bi-directional dynamic associative neural network

Derived from simple neural network models, a bidirectional dynamic associative neural network for tracking and predicting target motion is presented. The network applies a retrospective autoregression model for continual updating of the network parameters and computing the future motion states of the target. Simulation results show improvements over previous models in the accuracy of prediction