{"title":"听觉感知的时频神经网络分层模型","authors":"V.C. Georgopoulos, D. Preis","doi":"10.1109/ASPAA.1993.379981","DOIUrl":null,"url":null,"abstract":"This paper introduces a layered neural network model for hearing perception. It is based on five important perceptual properties of hearing. The neural network model processes a joint-domain representation of the input signal to yield the desired perceptual properties. The focus is on the first two layers of the model, the transformation layer and two feature extraction layers.<<ETX>>","PeriodicalId":270576,"journal":{"name":"Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics","volume":"3 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"1993-10-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"1","resultStr":"{\"title\":\"A time-frequency neutral network layered model for hearing perception\",\"authors\":\"V.C. Georgopoulos, D. Preis\",\"doi\":\"10.1109/ASPAA.1993.379981\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper introduces a layered neural network model for hearing perception. It is based on five important perceptual properties of hearing. The neural network model processes a joint-domain representation of the input signal to yield the desired perceptual properties. The focus is on the first two layers of the model, the transformation layer and two feature extraction layers.<<ETX>>\",\"PeriodicalId\":270576,\"journal\":{\"name\":\"Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics\",\"volume\":\"3 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"1993-10-17\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"1\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ASPAA.1993.379981\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of IEEE Workshop on Applications of Signal Processing to Audio and Acoustics","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ASPAA.1993.379981","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A time-frequency neutral network layered model for hearing perception
This paper introduces a layered neural network model for hearing perception. It is based on five important perceptual properties of hearing. The neural network model processes a joint-domain representation of the input signal to yield the desired perceptual properties. The focus is on the first two layers of the model, the transformation layer and two feature extraction layers.<>
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