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论文类型：会议论文

发表时间：2014-07-28

收录刊物：EI、CPCI-S、Scopus

页面范围：5065-5070

关键字：Multivariate Time Series; Square-root Cubature Kalman Filter; Echo State Network

摘要：Considering the problem of multivariate time series prediction, this paper proposes an online prediction model for multivariable time series by echo state network (ESN) based on square-root cubature Kalman filter. The model uses echo state network to map the nonlinear relationship between input and output, subsequently, updates the output weights of reservoir online by square-root cubature Kalman filter (SCKF) with three-order approximation for nonlinear functions. We add outlier detection into the filter algorithm, avoiding the adverse effect on the follow-up time series prediction. Experiment results on multivariate benchmark dataset and observed dataset demonstrate the effectiveness of the proposed model.