Pattern matching based on tensor multilinear pca for multivariate time series
Dong Hongy · Fuzhou daxue xuebao. Ziran kexue ban · 2015
Present a pattern matching method based on tensor multilinear principal component analysis for multivariate time series,the pattern matching method obtains the low dimensional reconstruction of multivariate time series by tensor multilinear principal component analysis and gets the pattern presentation of the multivariate time series. Our method uses the Frobenius norm as the measure of similarity between patterns. The experiment results show that the proposed method achieves higher matching accuracy and spends less time on four open multivariate time series datasets,and is suitable for different size datasets.