乘法函数
预处理器
信号(编程语言)
随机变量
计算机科学
算法
数学
统计
人工智能
随机变量
数学分析
程序设计语言
作者
Achim Köhler,Monika Zimonja,Vegard H. Segtnan,Harald Martens
出处
期刊:Elsevier eBooks
[Elsevier]
日期:2009-01-01
卷期号:: 139-162
被引量:32
标识
DOI:10.1016/b978-044452701-1.00102-2
摘要
This chapter describes the model-based preprocessing technique extended multiplicative signal correction (EMSC) and several of its applications in biospectroscopy. EMSC can be used for reducing a number of undesired effects in sample measurements, such as stochastic measurement noise, nonlinear instrument responses, shift problems as well as interfering effects of undesired chemical and physical variations that can create problems in multivariate calibration and in the interpretation of results. Many of these phenomena can be removed computationally by EMSC before subsequent data analysis. Here, several undesired effects are described together with respective EMSC data preprocessing and scaling techniques. Examples for applications of EMSC in biospectroscopy are provided.
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