Data Fusion of Multivariate Time Series Based on Local Maximum Weighted Coefficient

Abstract

In this paper, a novel fusion data algorithm is proposed via local Maximum weighted coefficient algorithm. For effectively fusing multivariate time series and reserving the motion information of original system, the weighted coefficients are rationally estimated the fusion state. Experimental results show that the algorithm can obtain desirable results on Lorenz model and multi-lead ECG signals.