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An Electronic Nose Recognition Algorithm Based on PCA-ICA Preprocessing and Fuzzy Neural Network

机译:一种基于PCA-ICA预处理和模糊神经网络的电子鼻识别算法

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摘要

To improve the recognition performance of electronic noses detecting gas mixtures, a PCA-ICA signal preprocessing and fuzzy neural network based recognition algorithm is proposed. In this approach, signals of electronic noses are firstly preprocessed effectively by combination of Principal Component Analysis (PCA) and Independent Component Analysis (ICA), and then processed with a fuzzy Takagi-Sugeno system integrated with multi neural networks for the purpose of quantification of gas concentrations. Experiment results show that the alcohol concentration recognition performance is highly improved in alcohol and gasoline mixtures even interfered by smokes.
机译:为了提高电子鼻窦检测气体混合物的识别性能,提出了一种PCA-ICA信号预处理和模糊神经网络的识别算法。在这种方法中,通过主成分分析(PCA)和独立分量分析(ICA)的组合首先有效地预处理电子鼻子的信号,然后用模糊Takagi-Sugeno系统进行处理,该系统集成了多神经网络,以定量气体浓度。实验结果表明,酒精浓度识别性能高度改善,甚至干涉烟碱。

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