Suchergebnisse - extended hierarchical multiinnovation stochastic gradient algorithm

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  1. 1

    Decomposition‐based multiinnovation gradient identification algorithms for a special bilinear system based on its input‐output representation von Wang, Longjin, Ji, Yan, Yang, Hualin, Xu, Ling

    ISSN: 1049-8923, 1099-1239
    Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 01.06.2020
    “… ‐based multiinnovation (ie, hierarchical multiinnovation) generalized extended stochastic gradient identification (H‐MI‐GESG …”
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    Journal Article
  2. 2

    Hierarchical multi-innovation generalised extended stochastic gradient methods for multivariable equation-error autoregressive moving average systems von Xu, Ling, Ding, Feng, Lu, Xian, Wan, Lijuan, Sheng, Jie

    ISSN: 1751-8644, 1751-8652
    Veröffentlicht: The Institution of Engineering and Technology 02.07.2020
    Veröffentlicht in IET control theory & applications (02.07.2020)
    “… ) algorithm, namely, hierarchical multi-innovation generalised extended stochastic gradient algorithm, is derived for the multivariable EEARMA systems through expanding the innovation vector to the innovation …”
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    Journal Article
  3. 3

    Maximum likelihood‐based gradient estimation for multivariable nonlinear systems using the multiinnovation identification theory von Xia, Huafeng, Ji, Yan, Xu, Ling, Alsaedi, Ahmed, Hayat, Tasawar

    ISSN: 1049-8923, 1099-1239
    Veröffentlicht: Bognor Regis Wiley Subscription Services, Inc 25.09.2020
    “… ‐based maximum likelihood recursive extended stochastic gradient algorithm with reduced computational complexity is presented to estimate all the parameters directly …”
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    Journal Article
  4. 4

    The iterative identification method for Hammerstein nonlinear channel von Su, Rui, Wang, Bin, Liu, Shigang

    ISBN: 1849198454, 9781849198455
    Veröffentlicht: Stevenage, UK IET 2014
    “… The extended hierarchical multi-innovation stochastic gradient algorithm is proposed by introducing multi-innovation identification theory and hierarchical principle to the extended stochastic gradient algorithm …”
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