Application of computational verb theory to gas recognition | |
Liu, Bin ; Liu, Yuan ; Cai, Daoping ; Wang, Taihong ; Yang, Tao ; Wang TH(王太宏) ; Yang T(杨涛) | |
2012 | |
关键词 | Acetone Chemical sensors Decision theory Ethanol Gas detectors Pattern recognition Sensors |
英文摘要 | Conference Name:2012 International Conference on Anti-Counterfeiting, Security and Identification, ASID 2012. Conference Address: Taipei, Taiwan. Time:August 24, 2012 - August 26, 2012.; Gas recognition techniques are important for metal oxide sensors in practical applications because of their poor selectivities. The conventional solution is using sensor arrays instead of single sensors for pattern recognition. But this solution is expensive and the accuracy is affected by every single sensor in it. So developing recognition techniques based on single sensors is strongly needed. In this paper, a new method based on computational verb theory was developed by employing verb similarities as decision features and a clear linear decision boundary was found. Precise recognition between ethanol and acetone was conducted by using a single sensor. Compared with the conventional gas recognition approach, this method is more cost effective and programmable which shows promising applications in future smart gas detecting systems. 漏 2012 IEEE. |
语种 | 英语 |
出处 | http://dx.doi.org/10.1109/ICASID.2012.6325294 |
出版者 | IEEE Computer Society |
内容类型 | 其他 |
源URL | [http://dspace.xmu.edu.cn/handle/2288/86771] ![]() |
专题 | 信息技术-会议论文 |
推荐引用方式 GB/T 7714 | Liu, Bin,Liu, Yuan,Cai, Daoping,et al. Application of computational verb theory to gas recognition. 2012-01-01. |
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