Artificial Neural Network-Based Algorithm for ARMA Model Order Estimation

被引：0
|
作者：
Al-Qawasmi, Khaled E. [1 ]
Al-Smadi, Adnan M. [2 ]
Al-Hamami, Alaa [1 ]
机构：
[1] Amman Arab Univ Grad Studies, Dept Comp Sci, Coll Informat Technol, Amman, Jordan
[2] Al Al-Bayt Univ, Dept Comp Sci, Coll Informat Technol, AlMafraq, Jordan
来源：
NETWORKED DIGITAL TECHNOLOGIES, PT 2 | 2010年 / 88卷
关键词：
Artificial Neural Networks; ANN; ARMA; Back-Propagation; Simulation; Eginevalue; System Identification; Signal Processing; Time Series; IDENTIFICATION; PREDICTION;
D O I：
暂无
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
This paper presents a new algorithm for the determination of the Auto-regressive 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.
引用
收藏
页码：184 / +
页数：3
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