期刊名称：International Journal of Multimedia and Ubiquitous Engineering
印刷版ISSN：1975-0080
出版年度：2015
卷号：10
期号：10
页码：75-82
DOI：10.14257/ijmue.2015.10.10.08
出版社：SERSC
摘要：In this article, a multi-tone signal generated by micro-speaker is adopted as the acoustic stimulation, and two microphones are used to collect the DPOAE data from human ear and background noise respectively. Otoacoustic emission is modeled based on Volterra kernel. The feature of human ear's DPOAE feature model is extracted intelligently by improved stimulation annealing genetic mixed algorithm. In order to apply this model feature to identification, its feasibility is verified by BP neural network. This provides a new biometric method for identity authentication.
