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基于径向基函数神经网络的智能嗅觉系统
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2009-07-10
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提出了基于智能嗅觉系统的识别混合有毒气体组分浓度的方法。该系统包括两大部分: 有毒气体传感器阵列模块和径向基函数神经网络模块。前者用于获取反映有毒气体组分的电信号, 后者用于提高识别混合有毒气体组分的选择性, 降低气体传感器阵列中各个敏感器件的交叉灵敏度。径向基函数神经网络具有很强的非线性并行处理能力和容错
能力, 实例分析取得了满意的测量结果。
关键词: 智能嗅觉系统; 径向基函数网络; 气体传感器阵列; 选择性
Abstract: Intelligent senso r array system is suggested to detect low concent rat ion of m ixed gases1 It is compo sed of two block s, that is gas senso r array and radial basis funct ion neural netwo rk (RBFNN ) 1 The fo rmer is used to acquire re2 sponse signal, and the later is used to imp rove the select ivity of the gas senso r1 RBFNN hasmo re advantage than BPNN ,
such as fault to lerance, nonlinear mapp ing etc, thus, it can overcome the cro ss2sensit ivity among heterogeneous gas sen2 so r and get mo re sat isfied measurement result1
Key words: intelligent o lfact ion system; radial basis funct ion netwo rk; gas senso r array; select ivity
能力, 实例分析取得了满意的测量结果。
关键词: 智能嗅觉系统; 径向基函数网络; 气体传感器阵列; 选择性
Abstract: Intelligent senso r array system is suggested to detect low concent rat ion of m ixed gases1 It is compo sed of two block s, that is gas senso r array and radial basis funct ion neural netwo rk (RBFNN ) 1 The fo rmer is used to acquire re2 sponse signal, and the later is used to imp rove the select ivity of the gas senso r1 RBFNN hasmo re advantage than BPNN ,
such as fault to lerance, nonlinear mapp ing etc, thus, it can overcome the cro ss2sensit ivity among heterogeneous gas sen2 so r and get mo re sat isfied measurement result1
Key words: intelligent o lfact ion system; radial basis funct ion netwo rk; gas senso r array; select ivity
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