一种新的基于粗集的辐射源信号识别模型

粗糙集理论作为一种新的处理含糊和不确定性问题的数学工具,已成为国际学术界的一个前沿的研究领域。在深入研究粗糙集理论的基础上,将其引入辐射源识别问题中,给出了一种基于粗糙集的辐射源信号识别模型。同时给出了一种不依赖先验知识确定辐射源识别权值的新方法,并提出了一种新的分类规则。最后,进行了计算机仿真实验,并与经典的模糊模式识别及统计模式识别方法进行了比较,实验结果证明了该方法的优势和有效性。

A Novel Rough Set Emitter Signal Recognition Model

Rough set theory is a relatively new soft computing tool to deal with vagueness and uncertainty,and is regarded as a field of leading edge.Rough set theory is deeply studied in this paper and introduced into the problem of emitter recognition,based on which a new emitter signal recognition model is presented.At the same time,a new method of determining weight coefficients is proposed,which is independent of a priori knowledge.And a new classification rule is also presented in this paper.At last,computer simulation of recognizing the emitter purpose is selected,and compared with classical fuzzy pattern recognition and statistical recognition algorithm through simulation.Experiments results demonstrate the excellent performance of this new recognition method as compared to existing two pattern recognition techniques.