Abstract
This chapter presents the concept and theory of independent component analysis (ICA). The method originated from signal processing research, where unknown signal sources are mixed to a new set of signals. This general objective of separating signals into pure sources is called blind source separation (BSS). ICA has been shown to be useful in solving the BSS problem, and if the pure sources are found, then also the mixing system may be estimated. Similar situations occur in chemometrics where the pure spectra of chemical compounds and their concentrations are observed with different type of instrumentation such as spectroscopy. The necessity of proper validation in ICA is emphasized and put into a chemometric framework. Examples on simulated as well as spectroscopic data are shown to illustrate the potential of ICA in chemometric applications.
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