Constrained nonlinear method for estimating component spectra from multicomponent mixtures
Applied Optics, Vol. 22, Issue 22, pp. 3599-3603 (1983)
http://dx.doi.org/10.1364/AO.22.003599
Acrobat PDF (562 KB)
Abstract
A method is described for estimating the spectra of pure components from the spectra of unknown mixtures with various relative concentrations. This method is based on principal component analysis and a constrained nonlinear optimization technique and is applicable to qualitative analysis of mixtures of more than three components. The method gives two curves as the estimate of a component spectrum: one consists of the set of the maxima and the other consists of the set of the minima for all sampling points subject to a priori information. Experimental results of the estimation of the infrared absorption spectra of xylene-isomer mixtures are shown; the noise problem with this method is also discussed.
© 1983 Optical Society of America
Citation
Keiji Sasaki, Satoshi Kawata, and Shigeo Minami, "Constrained nonlinear method for estimating component spectra from multicomponent mixtures," Appl. Opt. 22, 3599-3603 (1983)
http://www.opticsinfobase.org/ao/abstract.cfm?URI=ao-22-22-3599
You do not have subscription access to this journal. Citation lists with outbound citation links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Log in to access OSA Member Subscription
You do not have subscription access to this journal. Cited by links are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Log in to access OSA Member Subscription
You do not have subscription access to this journal. Article level metrics are available to subscribers only. You may subscribe either as an OSA member, or as an authorized user of your institution.
Contact your librarian or system administrator
or
Log in to access OSA Member Subscription





OSA is a member of 