Extracting experimental information from large matrixes. 1. A new algorithm for the application of matrix rank analysis

Gábor Peintler, István Nagypál, Attila Jancsó, Irving R. Epstein, Kenneth Kustin

Research output: Contribution to journalArticle

73 Citations (Scopus)

Abstract

For many, especially complex, systems, modern spectroscopic measurements can be generated as large experimental data sets in matrix form. We report a new algorithm for the application of matrix rank analysis to extract significant experimental information from these large matrixes. The algorithm may be used to detect and remove erroneous rows and/or columns from the matrixes and to monitor the most significant experimental information along the rows and/or columns of the data sets. A new method for determining the number of absorbing species and a new concept for the treatment of experimental errors are presented. The algorithm is illustrated on real experimental examples.

Original languageEnglish
Pages (from-to)8013-8020
Number of pages8
JournalJournal of Physical Chemistry A
Volume101
Issue number43
DOIs
Publication statusPublished - Oct 23 1997

    Fingerprint

ASJC Scopus subject areas

  • Physical and Theoretical Chemistry

Cite this