基于神经网络的气体检测模型实现研究

Tao Chi, Ming Chen
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引用次数: 0

摘要

本文提出了动物嗅觉系统的传导途径。模式识别被认为是智能的内在机制和基础,它建立在对大脑计算模式的模拟之上。根据这一观点,在气体检测装置中提出了从嗅觉器官中存在的计算模式到当前受嗅觉器官启发的计算机模拟模式的模式识别模块,该模块主要基于神经网络。该模块采用多功能传感器阵列建立在线感知的神经网络输入层。由于神经网络的识别训练,最终通过自学习和分析实现定性和数量的识别。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Study of Implementing the Model of Gas Inspection Based on Neural Networks
The conduction route of animal olfactory system has been proposed in this paper. Pattern recognition is considered as the inherent mechanism of the nature and the base of intelligence, which is established on simulation of brain computing pattern. According to this view, the pattern recognition module from computing pattern existing in the olfactory organs to current computer simulation mode inspired by the olfactory organs has been presented in gas inspection device, which mainly based on neutral networks. The module adopts the multi-function sensors array to establish the input layer of neutral networks for online perception. Due to the identification training of neutral networks the identification of qualitative and quantity is finally implemented through the self-learning and analysis.
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