Identification of Nonlinear System Based on Complex-Valued Flexible Neural Network

Identification of nonlinear system could help to understand and model the internal mechanism of real complex systems. In this paper, complex-valued version of flexible neural tree (CVFNT) model is proposed to identify nonlinear systems. In order to search the optimal structure and parameters of CVFNT model, a new hybrid evolutionary method based on structure-based evolutionary algorithm and firefly algorithm is employed. Two nonlinear system identification experiments are used to test CVFNT model. The results reveal that CVFNT model performs better than the proposed real-valued neural networks.

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