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《第36届中国控制会议论文集(A)》2017年
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The filtering based multi-innovation stochastic gradient algorithm for multi-input output-error systems

Jiling Ding  
【摘要】:In this paper, we discuss the identification problem of multi-input output-error moving average systems. A filtering based multi-innovation stochastic gradient algorithm with forgetting factors is derived by using the filtering technique with the multi-innovation identification theory, and a multi-innovation extended stochastic gradient algorithm is given for comparison.The simulation results confirm that the proposed algorithms can generate highly accurate parameter estimates compared with the multi-innovation stochastic gradient algorithm.
【作者单位】:Department of Mathematics, Jining University
【基金】:supported by Natural Science Foundation of Shandong province under Grant ZR2016FL08 the Science Foundation of Jining University,China under Grant 2016QNKJ01
【分类号】:N945.14
【正文快照】:
1 IntroductionSystem identification studies the theory and methods ofestablishing the mathematical models of systems[1].Pa-rameter estimation is widely applied in many fields,suchas biological control[2],engineering industry[3],networkcontrol[4,5],adapti

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