Abstract
Independent Component Analysis (ICA) is an emerging field of fundamental research with a wide range of applications such as remote sensing, data communications, speech processing and medical diagnosis. It is motivated by practical scenarios that involve multisources and multisensors. The key objective of ICA is to retrieve the source signals without resorting to any a priori information about the source signals and the transmission channel. ICA using second-order statistics and high-order statistics based techniques and the corresponding algorithms will be presented to perform the blind separation of stationary or cyclostationary sources. In the last part of the paper, a case study with real data having as subject dams displacements monitoring will be presented.
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Popescu, T.D. (2004). Independent Component Analysis with Application to Dams Displacements Monitoring. In: Voicu, M. (eds) Advances in Automatic Control. The Springer International Series in Engineering and Computer Science, vol 754. Springer, Boston, MA. https://doi.org/10.1007/978-1-4419-9184-3_19
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DOI: https://doi.org/10.1007/978-1-4419-9184-3_19
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