{"title":"一种新型中耳植入物的小波分频信号处理模块设计","authors":"Xiao-feng Min, Houguang Liu, N. Ta, Zhushi Rao","doi":"10.1109/MACE.2010.5536198","DOIUrl":null,"url":null,"abstract":"The wavelet transform separates the input signals into seventeen frequency bands based on Bark frequency scale. and each frequency band is multiplyed with the wavelet coefficients by the gain corresponding to the transform property of the human middle ear system. The results show this algorithm has a good performance of simulating the normal human middle ear","PeriodicalId":6349,"journal":{"name":"2010 International Conference on Mechanic Automation and Control Engineering","volume":"76 1","pages":"5282-5286"},"PeriodicalIF":0.0000,"publicationDate":"2010-06-26","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Wavelet frequency-division based signal processing module design for a new type of middle ear implant\",\"authors\":\"Xiao-feng Min, Houguang Liu, N. Ta, Zhushi Rao\",\"doi\":\"10.1109/MACE.2010.5536198\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"The wavelet transform separates the input signals into seventeen frequency bands based on Bark frequency scale. and each frequency band is multiplyed with the wavelet coefficients by the gain corresponding to the transform property of the human middle ear system. The results show this algorithm has a good performance of simulating the normal human middle ear\",\"PeriodicalId\":6349,\"journal\":{\"name\":\"2010 International Conference on Mechanic Automation and Control Engineering\",\"volume\":\"76 1\",\"pages\":\"5282-5286\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2010-06-26\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2010 International Conference on Mechanic Automation and Control Engineering\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/MACE.2010.5536198\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2010 International Conference on Mechanic Automation and Control Engineering","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/MACE.2010.5536198","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
Wavelet frequency-division based signal processing module design for a new type of middle ear implant
The wavelet transform separates the input signals into seventeen frequency bands based on Bark frequency scale. and each frequency band is multiplyed with the wavelet coefficients by the gain corresponding to the transform property of the human middle ear system. The results show this algorithm has a good performance of simulating the normal human middle ear