{"title":"基于分解算法的海豚生物声纳信号频率和能量差检测","authors":"M. W. Muller","doi":"10.4236/OJA.2016.61001","DOIUrl":null,"url":null,"abstract":"A set of dolphin echolocation signals previously collected from an Atlantic bottlenose dolphin in Kaneohe Bay, Hawai’i are decomposed using a matching pursuit algorithm to further investigate the role of four types of echolocation signals outlined elsewhere [1]. The method decomposes the echolocation signals into optimal linear expansions of waveforms, which are Gabor functions defined in a dictionary. The method allows for study of the changes in frequency content within a dolphin’s functional bandwidth during discrimination tasks. We investigate the role of the functional bandwidth in terms of the signal energy levels and echolocations task performance. Furthermore, ROC analysis is applied to the relative energies of the matched waveforms to determine probability of discrimination. The results suggest that dolphins may discriminate by inspection of the relevant frequency differences between targets. In addition, the results from the ROC analysis provides insight into the role of the different classes of dolphin signals and of the importance of modification of the outgoing echolocation clicks, which may be fundamental to a dolphin’s ability to identify and discriminate targets.","PeriodicalId":63563,"journal":{"name":"声学期刊(英文)","volume":"6 1","pages":"1-12"},"PeriodicalIF":0.0000,"publicationDate":"2016-03-29","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Frequency and Energy Difference Detection of Dolphin Biosonar Signals Using a Decomposition Algorithm\",\"authors\":\"M. W. Muller\",\"doi\":\"10.4236/OJA.2016.61001\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A set of dolphin echolocation signals previously collected from an Atlantic bottlenose dolphin in Kaneohe Bay, Hawai’i are decomposed using a matching pursuit algorithm to further investigate the role of four types of echolocation signals outlined elsewhere [1]. The method decomposes the echolocation signals into optimal linear expansions of waveforms, which are Gabor functions defined in a dictionary. The method allows for study of the changes in frequency content within a dolphin’s functional bandwidth during discrimination tasks. We investigate the role of the functional bandwidth in terms of the signal energy levels and echolocations task performance. Furthermore, ROC analysis is applied to the relative energies of the matched waveforms to determine probability of discrimination. The results suggest that dolphins may discriminate by inspection of the relevant frequency differences between targets. In addition, the results from the ROC analysis provides insight into the role of the different classes of dolphin signals and of the importance of modification of the outgoing echolocation clicks, which may be fundamental to a dolphin’s ability to identify and discriminate targets.\",\"PeriodicalId\":63563,\"journal\":{\"name\":\"声学期刊(英文)\",\"volume\":\"6 1\",\"pages\":\"1-12\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2016-03-29\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"声学期刊(英文)\",\"FirstCategoryId\":\"1089\",\"ListUrlMain\":\"https://doi.org/10.4236/OJA.2016.61001\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"声学期刊(英文)","FirstCategoryId":"1089","ListUrlMain":"https://doi.org/10.4236/OJA.2016.61001","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Frequency and Energy Difference Detection of Dolphin Biosonar Signals Using a Decomposition Algorithm
A set of dolphin echolocation signals previously collected from an Atlantic bottlenose dolphin in Kaneohe Bay, Hawai’i are decomposed using a matching pursuit algorithm to further investigate the role of four types of echolocation signals outlined elsewhere [1]. The method decomposes the echolocation signals into optimal linear expansions of waveforms, which are Gabor functions defined in a dictionary. The method allows for study of the changes in frequency content within a dolphin’s functional bandwidth during discrimination tasks. We investigate the role of the functional bandwidth in terms of the signal energy levels and echolocations task performance. Furthermore, ROC analysis is applied to the relative energies of the matched waveforms to determine probability of discrimination. The results suggest that dolphins may discriminate by inspection of the relevant frequency differences between targets. In addition, the results from the ROC analysis provides insight into the role of the different classes of dolphin signals and of the importance of modification of the outgoing echolocation clicks, which may be fundamental to a dolphin’s ability to identify and discriminate targets.