【摘要】 研究了Rough集和神经网络方法在信息融合目标识别中的应用 .提出将神经网络学习机制引入到Rough集系统 ,同时通过Rough集的条件和决策属性构造神经网络结构 ,并针对三种不同谱段下的三种不同目标图像进行了实验 ,试验表明 ,Rough集 神经网络相结合的识别算法的识别率要明显高于单独使用一种融合算法的识别率 ,训练时间也大大缩短 .更多还原

【Abstract】 The application of rough sets combined with neural network method in target recognition by data fusion is developed in this paper. The learning mechanism has been introduced into the rough sets system and the neural network is built up according to the attribute of conditions and the decision rules of the rough sets. Finally, the experiments with three different kinds of target images in three different kinds of spectrums shows that the combination of rough sets and neural network get a much higher recognition rate than taking one data fusion algorithm alone, also, the training time is reduced in large scale.更多还原