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Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms

Credit to Download: 1 | Page Numbers 8 | Abstract Views: 58
Year: 2015
COI code: JR_JACET-1-3_001
Paper Language: English

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Authors Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms

  Maryam Ashtari Mahini - Dept of Computer Engineering. Science and Research Branch, Islamic Azad University, Tehran, Iran.
  Mohammad Teshnehlab - Department of Computer Engineering, Science and Research Branch, Islamic Azad University, Tehran, Iran.
  Mojtaba Ahmadieh khanehsar - Department of Control Engineering, Semnan University, Semnan, Iran.

Abstract:

Neural networks are applicable in identification systems from input-output data. In this report, we analyze theHammerstein-Wiener models and identify them. TheHammerstein-Wiener systems are the simplest type of block orientednonlinear systems where the linear dynamic block issandwiched in between two static nonlinear blocks, whichappear in many engineering applications; the aim of nonlinearsystem identification by Hammerstein-Wiener neural networkis finding model order, state matrices and system matrices. Wepropose a robust approach for identifying the nonlinear systemby neural network and subspace algorithms. The subspacealgorithms are mathematically well-established and noniterativeidentification process. The use of subspace algorithmmakes it possible to directly obtain the state space model.Moreover the order of state space model is achieved usingsubspace algorithm. Consequently, by applying the proposedalgorithm, the mean squared error decreases to 0.01 which isless than the results obtained using most approaches in theliterature.

Keywords:

Neural Network, nonlinear system identification, Hammerstein-Wiener model, state space and subspace identification

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COI code: JR_JACET-1-3_001

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Ashtari Mahini, Maryam; Mohammad Teshnehlab & Mojtaba Ahmadieh khanehsar, 2015, Nonlinear System Identification Using Hammerstein-Wiener Neural Network and subspace algorithms, Journal of Advances in Computer Engineering and Technology 1 (3), https://www.civilica.com/Paper-JR_JACET-JR_JACET-1-3_001.htmlInside the text, wherever referred to or an achievement of this article is mentioned, after mentioning the article, inside the parental, the following specifications are written.
First Time: (Ashtari Mahini, Maryam; Mohammad Teshnehlab & Mojtaba Ahmadieh khanehsar, 2015)
Second and more: (Ashtari Mahini; Teshnehlab & Ahmadieh khanehsar, 2015)
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