Resolving overlapped GC-MS data using independent component analysis

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  Independent component analysis (ICA) is a statistical signal processing technique that aims at recovering the source signals under the assumption that the source signals are statistically independent.It has the potential applications on blind source separation (BSS) of multivariate signals and drawn great attentions.ICA has been applied to analytical chemical data analysis, medical signals processing, speech recognition, fault detection, statistic process monitoring, and batch processes monitoring, etc.
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