{"title":"频域分析","authors":"M. C. Arva","doi":"10.1109/ECAI.2016.7861127","DOIUrl":null,"url":null,"abstract":"In this paper it is presented the second stage analysis used to determine the signal quality coefficient for vibro-acoustic signals. After successfully determining the integrity coefficient in the “first stage analysis on determining the Signal Quality Coefficient in vibro-acoustic domain-waveform integrity analysis” paper a second and deeper analysis is presented. This is a frequency domain analysis and uses an algorithm of evaluating the spectral resemblance between two analyzed vibro-acoustic signals. Spectrum normalization method is used. By accessing the lost or gained information percentage of spectral components for the targeted signal, a Signal Quality Coefficient (SQC) is determined. The SQC frequency analysis returns a value (percentage) which describes the quality of “target” signal reported to the “reference” signal.","PeriodicalId":122809,"journal":{"name":"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","volume":"54 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2016-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"23","resultStr":"{\"title\":\"Frequency domain analysis\",\"authors\":\"M. C. Arva\",\"doi\":\"10.1109/ECAI.2016.7861127\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this paper it is presented the second stage analysis used to determine the signal quality coefficient for vibro-acoustic signals. After successfully determining the integrity coefficient in the “first stage analysis on determining the Signal Quality Coefficient in vibro-acoustic domain-waveform integrity analysis” paper a second and deeper analysis is presented. This is a frequency domain analysis and uses an algorithm of evaluating the spectral resemblance between two analyzed vibro-acoustic signals. Spectrum normalization method is used. By accessing the lost or gained information percentage of spectral components for the targeted signal, a Signal Quality Coefficient (SQC) is determined. The SQC frequency analysis returns a value (percentage) which describes the quality of “target” signal reported to the “reference” signal.\",\"PeriodicalId\":122809,\"journal\":{\"name\":\"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)\",\"volume\":\"54 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-06-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"23\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2016 8th International Conference on Electronics, Computers and Artificial Intelligence (ECAI)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ECAI.2016.7861127\",\"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 International Conference on Electronics, Computers and Artificial Intelligence (ECAI)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ECAI.2016.7861127","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
In this paper it is presented the second stage analysis used to determine the signal quality coefficient for vibro-acoustic signals. After successfully determining the integrity coefficient in the “first stage analysis on determining the Signal Quality Coefficient in vibro-acoustic domain-waveform integrity analysis” paper a second and deeper analysis is presented. This is a frequency domain analysis and uses an algorithm of evaluating the spectral resemblance between two analyzed vibro-acoustic signals. Spectrum normalization method is used. By accessing the lost or gained information percentage of spectral components for the targeted signal, a Signal Quality Coefficient (SQC) is determined. The SQC frequency analysis returns a value (percentage) which describes the quality of “target” signal reported to the “reference” signal.