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Maximum likelihood iterative identification approaches for multivariable equation-error moving average systems
The identification issues of a multivariable system with coloured noises are investigated in this paper. The decomposition strategy is utilised for dimension reduction by transforming a multivariable system into several sub-models. A maximum likelihood least squares-based iterative identification ap...
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Published in: | International journal of systems science 2020-12, Vol.51 (16), p.3285-3298 |
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container_title | International journal of systems science |
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creator | Xia, Huafeng Xie, Li Zhu, Quanmin |
description | The identification issues of a multivariable system with coloured noises are investigated in this paper. The decomposition strategy is utilised for dimension reduction by transforming a multivariable system into several sub-models. A maximum likelihood least squares-based iterative identification approach is presented to enhance the parameter estimation accuracy by combining the iterative identification technique with the maximum likelihood principle. A simulation example is offered to test the effectiveness of the proposed method. |
doi_str_mv | 10.1080/00207721.2020.1814893 |
format | article |
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subjects | decomposition iterative identification Iterative methods maximum likelihood Multivariable system Parameter estimation Parameter identification |
title | Maximum likelihood iterative identification approaches for multivariable equation-error moving average systems |
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