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本文用具有不同特性的非选择性气敏元件组成气敏陈列，结合神经网络模式识别和信息处理技术，进行混合气体识别和浓度定量检测。着重说明神经网络模式识别法在气敏阵列信号处理中的应用。
In this paper, a gas sensitive display is composed of non-selective gas sensors with different characteristics. Combined with neural network pattern recognition and information processing technology, gas mixture identification and concentration quantitative detection are carried out. Emphasis is placed on the application of neural network pattern recognition in gas sensor array signal processing.