Artificial neural network electronic nose for volatile organic compounds

被引:4
|
作者
Abdel-Aty-Zohdy, HS [1 ]
机构
[1] Oakland Univ, Dept Elect & Syst Engn, Microelect Syst Design Lab, Rochester, MI 48309 USA
关键词
D O I
10.1109/GLSV.1998.665211
中图分类号
TP3 [计算技术、计算机技术];
学科分类号
0812 ;
摘要
Advanced microsystems that include, sensors, interface-circuits, and pattern-recognition integrated monolithically or in a hybrid module are needed por civilian, military and space applications. These include: automotive, medical applications, environmental engineering, and manufacturing automation. ASICS with Artificial Neural Networks (ANN;I are considered in this paper, with the objective of recognizing air-borne volatile organic compounds, especially alcohols, ethers, esters, halocarbons, NH3, NO2, and other warfare agent simulants. The ASIC inputs are connected to the outputs from array-distributed sensors which measure, three-features for identifying each of four chemicals. A Specialized Reinforcement Neural Network (RNN) learning approach is chosen for the chemicals classification problem. Hardware implementation of the RNN is presented for 2 mu m CMOS process, MOSIS chip. Design implementation and evaluation are also presented.(1).
引用
收藏
页码:122 / 125
页数:4
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