Research on a new network model for temporal-spatial information fusion at decision level
Xiao Shun-ping · Systems engineering and electronics · 2008
Information fusion for target recognition can generate more accurate classification result than each of the constituent sensors.Because of the high information processing flexibility,fusion at decision level has become a research focus on information fusion.Aiming at the shortage of the common fusion scheme which cannot adapt itself to environment change,a new neural network model for temporal-spatial information fusion at decision level is put forward.The expert knowledge and environmental information are sufficiently used to initialize the network,and an on-line learning algorithm for the network's connected weights is given.Simulation result shows the efficiency of the new network's model.