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.
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Al-Qawasmi, K.E., Al-Smadi, A.M., Al-Hamami, A. (2010). Artificial Neural Network-Based Algorithm for ARMA Model Order Estimation. In: Zavoral, F., Yaghob, J., Pichappan, P., El-Qawasmeh, E. (eds) Networked Digital Technologies. NDT 2010. Communications in Computer and Information Science, vol 88. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-14306-9_19
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DOI: https://doi.org/10.1007/978-3-642-14306-9_19
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-642-14305-2
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