Sheng-Yu Peng, Yu-Chi Tsao, P. Hasler, David V. Anderson
{"title":"基于径向基函数的可编程模拟分类器","authors":"Sheng-Yu Peng, Yu-Chi Tsao, P. Hasler, David V. Anderson","doi":"10.1109/ICASSP.2008.4517887","DOIUrl":null,"url":null,"abstract":"A 16 x 16 programmable analog radial-basis-function (RBF) based classifier is demonstrated. The distribution of each feature is modeled by a Gaussian function, which is realized by a proposed floating-gate bump circuit having bell-shaped transfer characteristics. The maximum likelihood, mean, and variance of the distribution are stored in floating-gate transistors and are independently programmable. By cascading these floating-gate bump circuits, the overall transfer characteristics approximate a multivariate Gaussian distribution with a diagonal covariance matrix. An array of these circuits constitutes a compact RBF-based classifier. When followed by a winner-take-all circuit, the analog classifier can implement vector quantization. Automatic gender identification is implemented on a 16 x 16 analog vector quantizer chip as one possible audio application of this work. The performance of the analog classifier is comparable to that of digital counter -parts. The proposed approach can be at least two orders of magnitude more power efficient than the digital microprocessors at the same task.","PeriodicalId":333742,"journal":{"name":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","volume":null,"pages":null},"PeriodicalIF":0.0000,"publicationDate":"2008-05-12","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":"{\"title\":\"A programmable analog radial-basis-function based classifier\",\"authors\":\"Sheng-Yu Peng, Yu-Chi Tsao, P. Hasler, David V. Anderson\",\"doi\":\"10.1109/ICASSP.2008.4517887\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"A 16 x 16 programmable analog radial-basis-function (RBF) based classifier is demonstrated. The distribution of each feature is modeled by a Gaussian function, which is realized by a proposed floating-gate bump circuit having bell-shaped transfer characteristics. The maximum likelihood, mean, and variance of the distribution are stored in floating-gate transistors and are independently programmable. By cascading these floating-gate bump circuits, the overall transfer characteristics approximate a multivariate Gaussian distribution with a diagonal covariance matrix. An array of these circuits constitutes a compact RBF-based classifier. When followed by a winner-take-all circuit, the analog classifier can implement vector quantization. Automatic gender identification is implemented on a 16 x 16 analog vector quantizer chip as one possible audio application of this work. The performance of the analog classifier is comparable to that of digital counter -parts. The proposed approach can be at least two orders of magnitude more power efficient than the digital microprocessors at the same task.\",\"PeriodicalId\":333742,\"journal\":{\"name\":\"2008 IEEE International Conference on Acoustics, Speech and Signal Processing\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2008-05-12\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"6\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2008 IEEE International Conference on Acoustics, Speech and Signal Processing\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICASSP.2008.4517887\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2008 IEEE International Conference on Acoustics, Speech and Signal Processing","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICASSP.2008.4517887","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
A programmable analog radial-basis-function based classifier
A 16 x 16 programmable analog radial-basis-function (RBF) based classifier is demonstrated. The distribution of each feature is modeled by a Gaussian function, which is realized by a proposed floating-gate bump circuit having bell-shaped transfer characteristics. The maximum likelihood, mean, and variance of the distribution are stored in floating-gate transistors and are independently programmable. By cascading these floating-gate bump circuits, the overall transfer characteristics approximate a multivariate Gaussian distribution with a diagonal covariance matrix. An array of these circuits constitutes a compact RBF-based classifier. When followed by a winner-take-all circuit, the analog classifier can implement vector quantization. Automatic gender identification is implemented on a 16 x 16 analog vector quantizer chip as one possible audio application of this work. The performance of the analog classifier is comparable to that of digital counter -parts. The proposed approach can be at least two orders of magnitude more power efficient than the digital microprocessors at the same task.