Abstract: System identification is essential for modeling and control of nonlinear dynamic systems. In practice, traditional linear or unidirectional recurrent models often fail to capture the ...
Abstract: In nonlinear systems, the system response frequently fluctuates with the discrepancy of variation trends over a certain horizon. In this situation, type-2 fuzzy neural networks can be ...
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