کد مقاله کد نشریه سال انتشار مقاله انگلیسی نسخه تمام متن
382852 660794 2015 9 صفحه PDF دانلود رایگان
عنوان انگلیسی مقاله ISI
Nonlinear system identification using a cuckoo search optimized adaptive Hammerstein model
ترجمه فارسی عنوان
شناسایی سیستم غیرخطی با استفاده از مدل همرشتاین تطبیقی ​​بهینه سازی جستجوی کوکو
موضوعات مرتبط
مهندسی و علوم پایه مهندسی کامپیوتر هوش مصنوعی
چکیده انگلیسی


• A novel nonlinear system identification scheme is proposed.
• A Hammerstein model has been trained using cuckoo search algorithm.
• The model is a cascade of a FLANN and an adaptive IIR filter.
• Simulation study shows enhanced modeling capacity of the proposed scheme.
• The new schemes offers lesser computational time over other methods studied.

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.

ناشر
Database: Elsevier - ScienceDirect (ساینس دایرکت)
Journal: Expert Systems with Applications - Volume 42, Issue 5, 1 April 2015, Pages 2538–2546
نویسندگان
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