The application of data enhancement techniques to digitized spectra allows more efficient utilization of the information, resulting in increased sensitivity and selectivity. Chapter I discusses the techniques used in this study, including ensemble averaging, digital filtering, correlation, least squares fitting, and background treatments. / In Chapter II, a study of simultaneous multicomponent analysis by computer enhanced infrared spectroscopy is presented. Cross-correlation and least squares fitting are used in three-component analyses under comparable conditions. Simulations are carried out to evaluate the effect of noise, degree of peak overlap, degree of peak width similarities, and various errors on the results. Each method is then applied in the analysis of the three major classes of serum lipids. Statistical comparison shows that least squares fitting gives slightly better results than cross-correlation. / Chapter III discusses the determination of ('13)CO(,2)/('12)CO(,2) ratios by infrared spectroscopy employing cross-correlation and least squares fitting. Small increases in the levels of ('13)CO(,2) over naturally occurring levels, as are encountered in clinical breath tests, are measured. The results from cross-correlation are better than those by least squares in this application. / Source: Dissertation Abstracts International, Volume: 44-11, Section: B, page: 3395. / Thesis (Ph.D.)--The Florida State University, 1983.
| Identifer | oai:union.ndltd.org:fsu.edu/oai:fsu.digital.flvc.org:fsu_75237 |
| Contributors | TYSON, LESIA LINDA., Florida State University |
| Source Sets | Florida State University |
| Detected Language | English |
| Type | Text |
| Format | 84 p. |
| Rights | On campus use only. |
| Relation | Dissertation Abstracts International |
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