A simplified dynamic independent component analysis

The traditional principal component analysis(PCA) can not analyze dynamic process with the self-correlation information of the process variable.Moreover,the process data may not follow Gaussian distribution so as to cause the improper detection of PCA.Dynamic independent component analysis(DICA) has the ability to solve the problems above.In this paper,a simplified DICA approach is proposed based on the time lag of the dynamic process,correspondingly,the second order autoregressive models are used to validate the possibility of the method.The simulation results show that it is an efficient and simple method compared with DICA.