Method of Radar Target Recognition Based on GFMM Learning Neural Network
Zhang Qing-gui · Modern Radar · 2006
In order to further improve the ability of radar target recognition of Naval vessels with neural networks, a new unsupervised general fuzzy min-max(GFMM) learning network is put forward. This network is a new neural network with the ability of unsupervised training and cluster recognition, which inherits the merits of original general min-max network and adds the self-adjusted and on-line learning capacities which improve the logical net structure and arithmetic. The method of radar target recognition based on unsupervised general min-max learning neural network perfectly accomplishes the characteristic learning of radar target in an integrated process. The results of simulated application experiment in some naval coast radar target recognition indicate that the method based on unsupervised GFMM network is better than the conventional networks and possesses the wonderful applicability in the realm of radar target recognition.