电子鼻信号处理方法综述

具有模仿人的嗅觉系统的电子鼻在过去十年中发展迅速,大部分成果开始商业应用,主要应用于食品和化妆品行业。用于电子鼻系统的信号处理方法主要包括静特征分析法和动态特征处理方法。静态特征分析法包括主成分分析法,判别函数分析法,类聚分析法和基于网络的多层感知器。动态特征分析法包括传统的参数法和非参数法,非参数法是借助于传统的系统识别方式及线性滤波器、时间序列神经网络系统。

The overview of signal processing techniques in electronic noses

The field of electronic noses,electronic instruments capable of mimicking the human olfactory system,has developed rapidly in the past ten years.Most of the work published to date and commercial applications,which are mainly employed in the food and cosmetics industries.The signal processing techniques in electronic relate to the use of well established static and dynamic pattern analysis techniques such as principal components analysis,discriminant function analysis,cluster analysis and multilayer perceptron based neural networks.Dynamic signal processing techniques reported so far include traditional parametric and nonparametlic ones borrowed from the traditional field of system identification as well as linear filters,time series neural networks and others.