PSOM算法用于未知雷达信号分选

粒子群算法(PSO)和神经网络的有机结合是目前一个十分活跃的研究领域,为分类问题的研究提供了新的思路和方法。针对基本SOM算法聚类数目不确定、聚类效果不佳等问题,提出PSOM算法用于未知雷达信号分选,利用PSO的优化算法替代SOM的启发式训练,对基本SOM算法进行改进,最后通过仿真实验验证了该算法在未知雷达信号分选应用上的有效性。

The PSOM Algorithm for Unknown Radar Signal Sorting

Currently the combination between PSO and NN is a very active area of research, which provides new ideas and methods for sorting. The PSOM algorithm is put forward to unknown radar signal sorting for the basal SOM has many problems, such as uncertain number of clusters, poor clustering results and so on. The heuristic training of SOM is replaced by PSO which advances the basal SOM. Finally, the PSOM algorithm is verified to be effective in the area of unknown radar signal sorting according to the emulated experiments.