{"title":"用FPGA实现热敏电阻特性线性化的神经网络","authors":"D. Sonowal, M. Bhuyan","doi":"10.1109/ICDCSYST.2012.6188753","DOIUrl":null,"url":null,"abstract":"This paper presents an FPGA (Field Programmable Gate Array) implementation of an artificial neural network (ANN) for linearization of nonlinear characteristics of a thermistor. A feed forward ANN is used for linearization. The network is trained in MATLAB with back propagation algorithm; weights and biases are determined and then implemented in Spartan-III FPGA. Subroutines are developed for single precision floating point arithmetic in IEEE-754 format.","PeriodicalId":356188,"journal":{"name":"2012 International Conference on Devices, Circuits and Systems (ICDCS)","volume":"11 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2012-03-15","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"8","resultStr":"{\"title\":\"FPGA implementation of neural network for linearization of thermistor characteristics\",\"authors\":\"D. Sonowal, M. Bhuyan\",\"doi\":\"10.1109/ICDCSYST.2012.6188753\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"This paper presents an FPGA (Field Programmable Gate Array) implementation of an artificial neural network (ANN) for linearization of nonlinear characteristics of a thermistor. A feed forward ANN is used for linearization. The network is trained in MATLAB with back propagation algorithm; weights and biases are determined and then implemented in Spartan-III FPGA. Subroutines are developed for single precision floating point arithmetic in IEEE-754 format.\",\"PeriodicalId\":356188,\"journal\":{\"name\":\"2012 International Conference on Devices, Circuits and Systems (ICDCS)\",\"volume\":\"11 1\",\"pages\":\"0\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2012-03-15\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"8\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"2012 International Conference on Devices, Circuits and Systems (ICDCS)\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.1109/ICDCSYST.2012.6188753\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"\",\"JCRName\":\"\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"2012 International Conference on Devices, Circuits and Systems (ICDCS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/ICDCSYST.2012.6188753","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
FPGA implementation of neural network for linearization of thermistor characteristics
This paper presents an FPGA (Field Programmable Gate Array) implementation of an artificial neural network (ANN) for linearization of nonlinear characteristics of a thermistor. A feed forward ANN is used for linearization. The network is trained in MATLAB with back propagation algorithm; weights and biases are determined and then implemented in Spartan-III FPGA. Subroutines are developed for single precision floating point arithmetic in IEEE-754 format.
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