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Gradient-based iterative identification method for multivariate equation-error autoregressive moving average systems using the decomposition technique. (English) Zbl 1406.93358
Summary: This paper studies the parameter estimation problems of multivariate equation-error autoregressive moving average systems. Firstly, a gradient-based iterative algorithm is presented as a comparison. In order to improve the computational efficiency and the parameter estimation accuracy, a decomposition-based gradient iterative algorithm is presented by using the decomposition technique. The key is to transform an original system into two subsystems and to estimate the parameters of each subsystem, respectively. Compared with the gradient-based iterative algorithm, the decomposition-based algorithm requires less computational efforts, and the simulation results indicate that this algorithm is effective.

MSC:
93E12 Identification in stochastic control theory
93E10 Estimation and detection in stochastic control theory
93C35 Multivariable systems, multidimensional control systems
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