多气体传感器信号样条回归分析  

Spline Regression of Multi-gas Sensors

作　　者：滕炯华[1] 袁朝辉[2] 王磊[1] 

机构地区：[1]同济大学信息与控制工程系,上海200092 [2]西北工业大学自动控制系,陕西西安710072

出　　处：《同济大学学报（自然科学版）》2004年第6期792-794,共3页Journal of Tongji University:Natural Science

基　　金：国家自然科学基金资助项目 ( 60 172 0 76)

摘　　要：回归分析研究某一变量和其他有关变量的依赖关系 ,它利用观测数据建立变量之间的回归模型 ,并做出预报和控制 .目前 ,回归分析已广泛应用于工程、经济、金融、生物和医学等领域 .将样条回归分析方法用于电子鼻系统中多气体传感器信号的信息处理 ,针对牛肉样本建立了牛肉新鲜度样条回归模型 ,并对该模型进行了回归分析 ,给出了牛肉新鲜度预报值和估计区间 .研究结果表明 。Regressive analysis is a research of the dependent relations for a certain variable versus other related variables.It can establish the regressive model of the variables with the observation data to forecast and control.At present,regressive analysis has been widely used in various fields such as engineering,economics,biology,medicine,etc.In this paper the spline regressive analysis is used for the information processing of multi-gases sensor signals with the electronic nose system.The authors have established a spline regressive model of the freshness degree of beef based on the beef sample,and have done regressive analysis to the model,which has given the forecast value and the estimative interval of the degree of the freshness of the beef.The results of research show that spline regressive analysis can be used for the information processing of examining the degree of the freshness of the beef with the electronic nose system.

关 键 词：多气体传感器 信息处理 样条回归 牛肉新鲜度样条回归模型 

分 类 号：TP212[自动化与计算机技术—检测技术与自动化装置]