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Artificial Neural Network-Based Algorithm for ARMA Model Order Estimation

  • Khaled E. Al-Qawasmi
  • Adnan M. Al-Smadi
  • Alaa Al-Hamami
Part of the Communications in Computer and Information Science book series (CCIS, volume 88)

Abstract

This paper presents a new algorithm for the determination of the Autoregressive Moving Average (ARMA) model order based on Artificial Neural Network (ANN). The basic idea is to apply ANN to a special matrix constructed from the Minimum Eginevalue (MEV) criterion. The MEV criterion is based on a covariance matrix derived from the observed output data only. The input signal is unobservable. The proposed algorithm is based on training the MEV covariance matrix dataset using the back-propagation technique. Our goal is to develop a system based on ANN; hence, the model order can be selected automatically without the need of prior knowledge about the model or any human intervention. Examples are given to illustrate the significant improvement results.

Keywords

Artificial Neural Networks ANN ARMA Back-Propagation Simulation Eginevalue System Identification Signal Processing Time Series 

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Copyright information

© Springer-Verlag Berlin Heidelberg 2010

Authors and Affiliations

  • Khaled E. Al-Qawasmi
    • 1
  • Adnan M. Al-Smadi
    • 2
  • Alaa Al-Hamami
    • 1
  1. 1.Depatrment of Computer Science,College of Information TechnologyAmman Arab University for Graduate StudiesAmmanJordan
  2. 2.Depatrment of Computer Science, College of Information TechnologyAl Al-Bayt UniversityAl-MafraqJordan

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