Conference Proceedings

Parametric canonical correlation analysis

S Chen, S Wang, R Sinnott

2019 IEEE International Conference on Cloud Computing Technology and Science (CloudCom) | IEEE | Published : 2019

Abstract

Generally, suppose a wave is a linear combination of multiple basis(Not necessarily a sine or cosine waves, it could also be a wavelet, etc.), different types of waves may be similar on some basis, but vary greatly on a certain basis. To address this problem, we introduce a PCCA-based feature extraction method that extends canonical correlation analysis (CCA). The PCCA-based method can train efficient classifiers to rely on only a few samples for periodic signals with support for removing noisy signals. As a demonstration, an efficient system is implemented for the classification of electrocardiogram (ECG) signals by PCCA. The performance is measured using several normal and abnormal ECG sig..

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