哈尔滨工程大学学报2011，Vol.32Issue(6)：767-772,6.DOI:10.3969/j.issn.1006-7043.2011.06.013
q-高斯的SOM神经网络在雷达抗干扰效能评估中的应用
A q-Gaussian SOM neural network and its application for evaluation of the effectiveness of radar ECCM
摘要
Abstract
In order to increase the output space of neighborhood functions and enhance the neighborhood cooperation between neurons, a q -Gaussian self-organizing mapping ( SOM ) neural network was proposed for evaluation of the effectiveness of radar electronic counter-countermeasures ( ECCM ). A q-Gaussian function was taken as a neighborhood function in an SOM neural network, and the non-extensive entropic index q was larger to efficiently increase the output space of the q-Gaussian function. The non-extensive entropic index q was adjusted adaptively from large to small with the decreasing neighbor to balance the neurons' distant and close neighborhood cooperation ability. The simulation results of the effectiveness evaluation of the radar ECCM and instance tests show that the q-Gaussian SOM neural network can obtain 100% accurate results in evaluating effectiveness, a 5% higher accuracy rate both in clustering and classification than other SOM neural networks in pattern recognition; the validity and feasibility of the method are verified.关键词
效能评估/雷达抗干扰/SOM神经网络/q-高斯Key words
effectiveness evaluation/ radar ECCM/ self-organizing mapping neural network/ q -Gaussian分类
信息技术与安全科学引用本文复制引用
赵伟,伞冶..q-高斯的SOM神经网络在雷达抗干扰效能评估中的应用[J].哈尔滨工程大学学报,2011,32(6):767-772,6.基金项目
国家自然科学基金资助项目(60474069). （60474069）
