Model Variation Tests for Multivariable Nonlinear Models Including Neural Networks

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Billings, S.A. ; Zhu, Q.M. (1994)
  • Publisher: Department of Automatic Control and Systems Engineering
  • Subject:
    arxiv: Computer Science::Information Theory

A fast and concise MIMO nonlinear model validity test procedure is derived, based on higher order correlation functions, to form a global to local hierarchical validation diagnosis of identified MIMO linear and nonlinear models. The new procedure is applied to four MIMO nonlinear system models including a neural network training example to demonstrate the effectiveness of the tests.
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