Multivariate data analysis in electroanalytical chemistry

作     者：Richards, E Bessant, C Saini, S 

作者机构：Cranfield Univ Cranfield Ctr Analyt Sci Silsoe MK45 4DT Beds England 

出 版 物：《ELECTROANALYSIS》 (电解分析)

年 卷 期：2002年第14卷第22期

页      面：1533-1542页

核心收录：

学科分类：081704[工学-应用化学] 07[理学] 070304[理学-物理化学(含∶化学物理)] 08[工学] 0817[工学-化学工程与技术] 0703[理学-化学] 

主　　题：multivariate data analysis calibration classification principal components neural networks genetic algorithms 

摘      要：Data analysis is becoming an increasingly important aspect of electroanalytical chemistry, as voltammetric techniques and electrode arrays become ever more popular as diagnostic tools. Modern data analysis techniques promise to help us make full use of the large amounts of data collected, allowing electroanalytical chemists to get more out of their existing instruments, and paving the way for new measurement approaches. Ibis article provides an overview of the most widely used multivariate techniques in electroanalysis, citing specific examples of how they have been applied, and looking at their relative merits. As in other areas of analytical science, no single technique is applicable to all applications and the running of controls and appreciation of the applications and limitations of each technique is essential.