Applying Neural Network Algorithm to Radar Track Compress Technique
作者单位：Department of Electrical EngineeringDa-Yeh University Chang-Hua
会议名称：《2005年海峡两岸三地无线科技学术会》
会议日期：2005年
学科分类：080904[工学-电磁场与微波技术] 0810[工学-信息与通信工程] 0809[工学-电子科学与技术（可授工学、理学学位）] 08[工学] 081105[工学-导航、制导与控制] 081001[工学-通信与信息系统] 081002[工学-信号与信息处理] 0825[工学-航空宇航科学与技术] 0811[工学-控制科学与工程]
关 键 词：Competitive Hopfield neural network Compressing radar tracks
摘 要：In this paper, a method using a Competitive Hopfield Neural Network (CHNN) is proposed for compressing radar tracks. Based on the CHNN, the compressing radar track is regarded as a minimization of a criterion function which is defined as the arc-to-chord deviation between the curve and the polygon. The CHNN differs from the original Hopfield network in that a competitive winner-take-all mechanism is *** winner-take-all mechanism adeptly precludes the necessity of determining the values for the weighting factors in the energy function in maintaining a feasible result. In order to prove the performance, a computer simulation algorithm is proposed in this paper. Computer simulation results indicate that this approach successfully obtains the compressed radar track.