Data filtering based stochastic gradient algorithms for multivariable CARAR-like systems

    Dongqing Wang Info
    Tong Shan Info
    Rui Ding Info
DOI: https://doi.org/10.3846/13926292.2013.804889

Abstract

This paper considers identification problems for a multivariable controlled autoregressive system with autoregressive noises. A hierarchical generalized stochastic gradient algorithm and a filtering based hierarchical stochastic gradient algorithm are presented to estimate the parameter vectors and parameter matrix of such multivariable colored noise systems, by using the hierarchical identification principle. The simulation results show that the proposed hierarchical gradient estimation algorithms are effective.

Keywords:

parameter identification, mathematical model, error estimates

How to Cite

Wang, D., Shan, T., & Ding, R. (2013). Data filtering based stochastic gradient algorithms for multivariable CARAR-like systems. Mathematical Modelling and Analysis, 18(3), 374-385. https://doi.org/10.3846/13926292.2013.804889

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June 1, 2013
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2013-06-01

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How to Cite

Wang, D., Shan, T., & Ding, R. (2013). Data filtering based stochastic gradient algorithms for multivariable CARAR-like systems. Mathematical Modelling and Analysis, 18(3), 374-385. https://doi.org/10.3846/13926292.2013.804889

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