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    Nonlinear System Identification With Gaussian Processes Using Laguerre and Kautz Filters1 

    Source: ASME Letters in Dynamic Systems and Control:;2025:;volume( 005 ):;issue: 004:;page 41001-1
    Author(s): Illg, Christopher; Balar, Nishilkumar; Nelles, Oliver
    Publisher: The American Society of Mechanical Engineers (ASME)
    Abstract: System identification can be used to determine data-driven mathematical models of dynamic processes. For nonlinear processes, model architectures that are as flexible as possible are required. One possibility is to utilize ...
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    DSpace software copyright © 2002-2015  DuraSpace
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