{"title":"主动回波分类的神经网络","authors":"J. Maksym","doi":"10.1109/ICASSP.1995.479764","DOIUrl":null,"url":null,"abstract":"The paper explores the use of an artificial neural network to distinguish between echoes from a constellation of acoustic reflectors representing a target and similar echoes produced by other reflectors, e.g. reverberation. The network was both trained and tested with simulated data. A wide band linear frequency modulated pulse was used in order to resolve the highlights of the target.","PeriodicalId":300119,"journal":{"name":"1995 International Conference on Acoustics, Speech, and Signal Processing","volume":"13 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1995-05-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"Neural networks for active echo classification\",\"authors\":\"J. Maksym\",\"doi\":\"10.1109/ICASSP.1995.479764\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The paper explores the use of an artificial neural network to distinguish between echoes from a constellation of acoustic reflectors representing a target and similar echoes produced by other reflectors, e.g. reverberation. The network was both trained and tested with simulated data. A wide band linear frequency modulated pulse was used in order to resolve the highlights of the target.\",\"PeriodicalId\":300119,\"journal\":{\"name\":\"1995 International Conference on Acoustics, Speech, and Signal Processing\",\"volume\":\"13 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1995-05-09\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"1995 International Conference on Acoustics, Speech, and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.1995.479764\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"1995 International Conference on Acoustics, Speech, and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.1995.479764","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
The paper explores the use of an artificial neural network to distinguish between echoes from a constellation of acoustic reflectors representing a target and similar echoes produced by other reflectors, e.g. reverberation. The network was both trained and tested with simulated data. A wide band linear frequency modulated pulse was used in order to resolve the highlights of the target.