期刊
EXPERT SYSTEMS WITH APPLICATIONS
卷 42, 期 5, 页码 2538-2546出版社
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.eswa.2014.10.040
关键词
Hammerstein model; System identification; Particle swarm optimization algorithm; Differential evolution; Cuckoo search algorithm
类别
资金
- Department of Science and Technology, Government of India [IFA-13 ENG-45]
An attempt has been made in this paper to model a nonlinear system using a Hammerstein model. The Hammerstein model considered in this paper is a functional link artificial neural network (FLANN) in cascade with an adaptive infinite impulse response (IIR) filter. In order to avoid local optima issues caused by conventional gradient descent training strategies, the model has been trained using a cuckoo search algorithm (CSA), which is a recently proposed stochastic algorithm. Modeling accuracy of the proposed scheme has been compared with that obtained using other popular evolutionary computing algorithms for the Hammerstein model. Enhanced modeling capability of the CSA based scheme is evident from the simulation results. (C) 2014 Elsevier Ltd. All rights reserved.
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