Feature-level signal processing for odor sensor arrays

T. Roppel, K. Dunman, M. Padgett, D. Wilson, T. Lindblad
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引用次数: 4

Abstract

A recurrent back-propagation neural algorithm is trained to classify nine odors. The algorithm is capable of correctly identifying the odors regardless of the time sequence of presentation. The classification is performed in near-real time and is based upon the transient response of an array of 15 tin-oxide gas sensors.
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气味传感器阵列的特征级信号处理
训练了一种循环反向传播神经算法来对九种气味进行分类。无论呈现的时间顺序如何,该算法都能够正确识别气味。该分类是基于15个氧化锡气体传感器阵列的瞬态响应,近乎实时地进行的。
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