The Hierarchical Iterative Identification Algorithm for Multi-Input-Output-Error Systems with Autoregressive Noise

Author

Ding, Jiling

Source

Complexity

Issue

Vol. 2017, Issue 2017 (31 Dec. 2017), pp.1-11, 11 p.

Publisher

Hindawi Publishing Corporation

Publication Date

2017-10-29

Country of Publication

Egypt

No. of Pages

11

Main Subjects

Philosophy

Abstract EN

This paper considers the identification problem of multi-input-output-error autoregressive systems.

A hierarchical gradient based iterative (H-GI) algorithm and a hierarchical least squares based iterative (H-LSI) algorithm are presented by using the hierarchical identification principle.

A gradient based iterative (GI) algorithm and a least squares based iterative (LSI) algorithm are presented for comparison.

The simulation results indicate that the H-LSI algorithm can obtain more accurate parameter estimates than the LSI algorithm, and the H-GI algorithm converges faster than the GI algorithm.

American Psychological Association (APA)

Ding, Jiling. 2017. The Hierarchical Iterative Identification Algorithm for Multi-Input-Output-Error Systems with Autoregressive Noise. Complexity،Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1143033

Modern Language Association (MLA)

Ding, Jiling. The Hierarchical Iterative Identification Algorithm for Multi-Input-Output-Error Systems with Autoregressive Noise. Complexity No. 2017 (2017), pp.1-11.
https://search.emarefa.net/detail/BIM-1143033

American Medical Association (AMA)

Ding, Jiling. The Hierarchical Iterative Identification Algorithm for Multi-Input-Output-Error Systems with Autoregressive Noise. Complexity. 2017. Vol. 2017, no. 2017, pp.1-11.
https://search.emarefa.net/detail/BIM-1143033

Data Type

Journal Articles

Language

English

Notes

Includes bibliographical references

Record ID

BIM-1143033