Order selection criteria for two-dimensional autoregressive model

IF 3.4 2区工程技术 Q2 ENGINEERING, ELECTRICAL & ELECTRONIC

Signal Processing Pub Date : 2025-01-23 DOI:10.1016/j.sigpro.2025.109909

Mohammadamin Rastegar, Mahmood Karimi, Mostafa Derakhtian

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引用次数: 0

Abstract

Most of the existing Autoregressive (AR) order selection criteria have very poor performance in the finite sample situation. Two well-known examples of such criteria are the Final Prediction Error (FPE) criterion and the Akaike Information Criterion (AIC). In this paper, the case where the region of support for parameters is the first quadrant Quarter Plane (QP) is considered, and modified versions of the AIC and FPE criteria for two-dimensional (2-D) AR model order selection are proposed for this case. In addition, the Exponentially Embedded Family (EEF) criterion for 2-D AR order selection is derived for this case. Performance of the proposed criteria and the existing criteria is evaluated and compared through numerical simulations. The results of these comparisons prove that the proposed AIC and FPE criteria perform much better than the existing versions of these criteria in the finite sample situation. Furthermore, these comparisons reveal that the proposed AIC criterion outperforms all examined criteria in the finite sample situation.

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来源期刊

Signal Processing 工程技术-工程：电子与电气

CiteScore

9.20

自引率

9.10%

发文量

309

审稿时长

41 days

期刊介绍： Signal Processing incorporates all aspects of the theory and practice of signal processing. It features original research work, tutorial and review articles, and accounts of practical developments. It is intended for a rapid dissemination of knowledge and experience to engineers and scientists working in the research, development or practical application of signal processing. Subject areas covered by the journal include: Signal Theory; Stochastic Processes; Detection and Estimation; Spectral Analysis; Filtering; Signal Processing Systems; Software Developments; Image Processing; Pattern Recognition; Optical Signal Processing; Digital Signal Processing; Multi-dimensional Signal Processing; Communication Signal Processing; Biomedical Signal Processing; Geophysical and Astrophysical Signal Processing; Earth Resources Signal Processing; Acoustic and Vibration Signal Processing; Data Processing; Remote Sensing; Signal Processing Technology; Radar Signal Processing; Sonar Signal Processing; Industrial Applications; New Applications.