{"title":"利用形态模式谱评价电磁环境的复杂程度","authors":"Dong Jun, Li Bing, Chen Shuangshuang, H. Hui","doi":"10.1109/ICCSN.2016.7586595","DOIUrl":null,"url":null,"abstract":"In this work, a novel feature extraction technique for evaluating the complexity degree of Electromagnetic Environment (EME) is proposed by utilizing the morphological pattern spectrum (MPS) based on the mathematical morphology theory. Four types of morphological operators, mean the morphological dilate, morphological erosion, morphological open and morphological close, are utilized for computing the MPS. EME signals with four complexity degree are simulated to evaluate the effectiveness of the presented method. Experimental results have demonstrated the MPS calculated by morphological erosion operator to be very effective for discriminating the complexity degree of EME.","PeriodicalId":158877,"journal":{"name":"2016 8th IEEE International Conference on Communication Software and Networks (ICCSN)","volume":"4 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"2","resultStr":"{\"title\":\"Evaluating the complexity degree of electromagnetic environment utilizing morphological pattern spectrum\",\"authors\":\"Dong Jun, Li Bing, Chen Shuangshuang, H. Hui\",\"doi\":\"10.1109/ICCSN.2016.7586595\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this work, a novel feature extraction technique for evaluating the complexity degree of Electromagnetic Environment (EME) is proposed by utilizing the morphological pattern spectrum (MPS) based on the mathematical morphology theory. Four types of morphological operators, mean the morphological dilate, morphological erosion, morphological open and morphological close, are utilized for computing the MPS. EME signals with four complexity degree are simulated to evaluate the effectiveness of the presented method. Experimental results have demonstrated the MPS calculated by morphological erosion operator to be very effective for discriminating the complexity degree of EME.\",\"PeriodicalId\":158877,\"journal\":{\"name\":\"2016 8th IEEE International Conference on Communication Software and Networks (ICCSN)\",\"volume\":\"4 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"2\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 8th IEEE International Conference on Communication Software and Networks (ICCSN)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICCSN.2016.7586595\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2016 8th IEEE International Conference on Communication Software and Networks (ICCSN)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICCSN.2016.7586595","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Evaluating the complexity degree of electromagnetic environment utilizing morphological pattern spectrum
In this work, a novel feature extraction technique for evaluating the complexity degree of Electromagnetic Environment (EME) is proposed by utilizing the morphological pattern spectrum (MPS) based on the mathematical morphology theory. Four types of morphological operators, mean the morphological dilate, morphological erosion, morphological open and morphological close, are utilized for computing the MPS. EME signals with four complexity degree are simulated to evaluate the effectiveness of the presented method. Experimental results have demonstrated the MPS calculated by morphological erosion operator to be very effective for discriminating the complexity degree of EME.