摘要
传统的定位识别方法,采用网络数据库包络切片对待定位的模糊信息进行能量聚集,在此过程中易受到外界环境干扰,导致模糊数据的定位准确率低、速度慢。对此,提出新的电子通信网络模糊信息自适应定位识别方法。构建电子通信网络模糊信息数据库,对模糊信息进行时频特征提取;将时频特征属性值转换为数值,完成对所有模糊信息数字特征的归一化处理;利用Fisher线性分析法对归一化处理后的模糊信息数字特征进行分类,实现模糊信息自适应定位识别。仿真结果证明,所提的方法相对于传统方法,模糊信息定位速度更快、更准确。
Traditionally,the location recognition method uses the envelope slice of network database to gather the energy of fuzzy information.In this process,it is easy to be interfered by the external environment,resulting in low accuracy and speed.Therefore,a new method of self-adaptive location and recognition for fuzzy information in electronic communication network was proposed.Firstly,the fuzzy information database of electronic communication network was constructed to extract the time-frequency feature of fuzzy information.Secondly,the attribute values of time-frequency characteristic were converted into the numerical value to normalize all the digital features of fuzzy information.Thirdly,Fisher linear analysis method was used to classify the digital features of the normalized fuzzy information.Finally,the self-adaptive location and recognition of fuzzy information was achieved.Simulation results show that the proposed method is faster and more accurate than the traditional method.
作者
周毅
ZHOU Yi(Sias International University,Zhengzhou University,Xinzheng Henan 451150,China)
出处
《计算机仿真》
北大核心
2019年第12期451-454,463,共5页
Computer Simulation
基金
2019年河南省科技厅省重点研发与推广项目(192102310452)
2018年河南省科技厅省重点研发与推广项目(科技攻关)(182102310864)
河南省教育厅人文社会科学研究项目(2019-ZDJH-152)
关键词
电子通信网络
模糊信息
自适应
定位识别
Electronic communication network
Fuzzy information
self-adaptive
Location recognition
