Recovering Independent Components from Shifted Data Using Fast Independent Component Analysis and Swarm Intelligence
Abstract:Frequency displacement, or spectral shift, is commonly observed in industrial spectral measurements. It can be caused by many factors such as sensor de-calibration or by external influences, which include changes in temperature. The presence of frequency displacement in spectral measurements can cause difficulties when statistical techniques, such as independent component analysis (ICA), are used to analyze it. Using simulated spectral measurements, this paper initially highlights the effect that frequency displacement has on ICA. A post-processing technique, employing particle swarm optimization (PSO), is then proposed that enables ICA to become robust to frequency displacement in spectral measurements. The capabilities of the proposed approach are illustrated using several simulated examples and using tablet data from a pharmaceutical application.
Document Type: Research Article
Affiliations: Control Systems Centre, School of Electrical and Electronic Engineering, University of Manchester, P.O. Box 88, Sackvile Street Building, Manchester, M60 1QD UK
Publication date: October 1, 2009
More about this publication?
- The Society publishes the internationally recognized, peer reviewed journal, Applied Spectroscopy, which is available both in print and online. Subscriptions are included with membership or can be purchased by institutional or corporate organizations. Abstracts may be viewed free of charge. Previously published as Bulletin (Society for Applied Spectroscopy)
- Editorial Board
- Information for Authors
- Submit a Paper
- Subscribe to this Title
- Membership Information
- Request copyrighted SAS materials
- Spectroscopic Nomenclature
- Focal Point (Open Access)
- ingentaconnect is not responsible for the content or availability of external websites