EXIN CCA is an extension of the Curvilinear Component Analysis (CCA), which solves for the noninvariant CCA projection and allows representing data drawn under different operating conditions. It can be applied to data visualization, interpretation (as a kind of sensor of the underlying physical phenomenon) and classification for real time industrial applications. Here an example is given for bearing fault diagnostics in an electromechanical device.
CitationCirrincione, [et al.]. Bearing fault diagnosis by EXIN CCA. A: International Joint Conference on Neural Networks. "The 2012 International Joint Conference on Neural Networks (IJCNN): Brisbane, Australia (June 10-15, 2012)". Brisbane: IEEE Computer Society Publications, 2012, p. 1-7.
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