CSE: Complex-Valued System With Evolutionary Algorithm

Complex-valued system identification has the ability to provide the basis for system analysis.So as to demonstrate the potential and internal mechanism of the complex-valued system, this paper proposes a novel complex-valued hybrid evolutionary (CSE) 14765-prb-a01 algorithm to optimize the complex-valued expression model (CEM).Complex-valued gene expression programming (CVGEP) is proposed to optimize the architectures of the CEM.

Complex-valued water wave optimization (CVWWO) is first proposed to optimize complex-valued coefficients and constants of the CEM.The two artificial complex-valued function approximation problems and non-minimum phase equalization problem are utilized to test the performance of the proposed algorithm.The results demonstrate that this method could triopods identify complex-valued systems more correctly than complex-valued neural networks, which could obtain above 90% smaller mean-squared error (MSE) performance than other complex-valued models.

With 10% Gaussian white noise, the CSE could identify accurate complex-valued structure and parameters containing coefficients and constants.The CVWWO has better convergence performance than complex-valued particle swarm optimization and crow search algorithm.

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