摘要
针对智能传感器侦察网络中的地面目标识别问题,提出了一种基于智能计算方法的地面目标声信号识别算法。基于智能计算方法设计识别系统,直接利用信号特征的变化范围作为分类特征,并结合能够处理定性输入的粗神经网络分类算法,有效地克服目标信号的不确定性问题,提高识别系统的识别率和稳定性。
Aimed at target identification problems of intelligent sensor reconnaissance networks, a ground object sound signal identification algorithm based on intelligent computation method is proposed. Based on recognition system of the intelligent computational method, the signal characteristics＇s variation range is used directly for chassified characteristics. The thick neural network sorting algorithm is integrated to process the qualitative input. The target signal＇ s uncertainty problem is overcomed effectively and recognition system＇ s recognition rate and the stability are enhanced largely.
出处
《传感器与微系统》
CSCD
北大核心
2009年第12期96-99,共4页
Transducer and Microsystem Technologies
基金
国家自然科学基金资助项目(50874059)
辽宁省科技攻关计划资助项目(2007231003)
关键词
粗集理论
粗神经网络
声信号识别
rough set（RS） theory
rough neural networks
sound signal recognition
