IEICE TRANSACTIONS on Fundamentals
An ARMA Order Selection Method with Fuzzy Theorem
Summary :
In this paper, an ARMA order selection method is proposed with a fuzzy reasoning method. In order to identify the reference model with the ARMA model, we need to determine its ARMA order. A less or more ARMA order, other than a suitable order causes problems such as; lack of spectral information, increasing calculation cost, etc. Therefore, ARMA order selection is significant for a high accurate ARMA model identification. The proposed method attempts to select an ARMA order of a time-varying model with the following procedures: (1) Suppose the parameters of the reference model change slowly, by introducing recursive fuzzy reasoning method, the estimated order is selected. (2) By introducing a fuzzy c-mean clustering methed, the period of the time during which the reference model is changing is detected and the forgetting factor of the recursive fuzzy reasoning method is set. Further, membership functions used in our algorithm are original, which are realized by experiments. In this paper, experiments are documented in order to validate the performance of the proposed method.
- Publication
- IEICE TRANSACTIONS on Fundamentals Vol.E77-A No.6 pp.937-943
- Publication Date
- 1994/06/25
- Publicized
- Online ISSN
- DOI
- Type of Manuscript
- Special Section PAPER (Special Section of Papers Selected from 1993 Joint Technical Conference on Circuits/Systems, Computers and Communications (JTC-CSCC'93))
- Category
- Digital Signal Processing
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Miki HASEYAMA, Hideo KITAJIMA, Masafumi EMURA, Nobuo NAGAI, "An ARMA Order Selection Method with Fuzzy Theorem" in IEICE TRANSACTIONS on Fundamentals,
vol. E77-A, no. 6, pp. 937-943, June 1994, doi: .
Abstract: In this paper, an ARMA order selection method is proposed with a fuzzy reasoning method. In order to identify the reference model with the ARMA model, we need to determine its ARMA order. A less or more ARMA order, other than a suitable order causes problems such as; lack of spectral information, increasing calculation cost, etc. Therefore, ARMA order selection is significant for a high accurate ARMA model identification. The proposed method attempts to select an ARMA order of a time-varying model with the following procedures: (1) Suppose the parameters of the reference model change slowly, by introducing recursive fuzzy reasoning method, the estimated order is selected. (2) By introducing a fuzzy c-mean clustering methed, the period of the time during which the reference model is changing is detected and the forgetting factor of the recursive fuzzy reasoning method is set. Further, membership functions used in our algorithm are original, which are realized by experiments. In this paper, experiments are documented in order to validate the performance of the proposed method.
URL: https://global.ieice.org/en_transactions/fundamentals/10.1587/e77-a_6_937/_p
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@ARTICLE{e77-a_6_937,
author={Miki HASEYAMA, Hideo KITAJIMA, Masafumi EMURA, Nobuo NAGAI, },
journal={IEICE TRANSACTIONS on Fundamentals},
title={An ARMA Order Selection Method with Fuzzy Theorem},
year={1994},
volume={E77-A},
number={6},
pages={937-943},
abstract={In this paper, an ARMA order selection method is proposed with a fuzzy reasoning method. In order to identify the reference model with the ARMA model, we need to determine its ARMA order. A less or more ARMA order, other than a suitable order causes problems such as; lack of spectral information, increasing calculation cost, etc. Therefore, ARMA order selection is significant for a high accurate ARMA model identification. The proposed method attempts to select an ARMA order of a time-varying model with the following procedures: (1) Suppose the parameters of the reference model change slowly, by introducing recursive fuzzy reasoning method, the estimated order is selected. (2) By introducing a fuzzy c-mean clustering methed, the period of the time during which the reference model is changing is detected and the forgetting factor of the recursive fuzzy reasoning method is set. Further, membership functions used in our algorithm are original, which are realized by experiments. In this paper, experiments are documented in order to validate the performance of the proposed method.},
keywords={},
doi={},
ISSN={},
month={June},}
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TY - JOUR
TI - An ARMA Order Selection Method with Fuzzy Theorem
T2 - IEICE TRANSACTIONS on Fundamentals
SP - 937
EP - 943
AU - Miki HASEYAMA
AU - Hideo KITAJIMA
AU - Masafumi EMURA
AU - Nobuo NAGAI
PY - 1994
DO -
JO - IEICE TRANSACTIONS on Fundamentals
SN -
VL - E77-A
IS - 6
JA - IEICE TRANSACTIONS on Fundamentals
Y1 - June 1994
AB - In this paper, an ARMA order selection method is proposed with a fuzzy reasoning method. In order to identify the reference model with the ARMA model, we need to determine its ARMA order. A less or more ARMA order, other than a suitable order causes problems such as; lack of spectral information, increasing calculation cost, etc. Therefore, ARMA order selection is significant for a high accurate ARMA model identification. The proposed method attempts to select an ARMA order of a time-varying model with the following procedures: (1) Suppose the parameters of the reference model change slowly, by introducing recursive fuzzy reasoning method, the estimated order is selected. (2) By introducing a fuzzy c-mean clustering methed, the period of the time during which the reference model is changing is detected and the forgetting factor of the recursive fuzzy reasoning method is set. Further, membership functions used in our algorithm are original, which are realized by experiments. In this paper, experiments are documented in order to validate the performance of the proposed method.
ER -
English
