Characterization of dynamic system nonlinearities via probabilistic approach

H. E. Emara-Shabaik; K. A.F. Moustafa

doi:10.1080/00207729408928983

Characterization of dynamic system nonlinearities via probabilistic approach

H. E. Emara-Shabaik
, K. A.F. Moustafa

Research output: Contribution to journal › Article › peer-review

5 Citations (Scopus)

Abstract

The problem of nonlinearity detection in system identification is treated. A probabilistic approach is taken which facilitates the analysis and enables the treatment of both strong and weak nonlinearities. The analysis shows that third- and fourth-order cumulants of the system output can be used to detect the existence of system nonlinearities, and to characterize their type

Original language	English
Pages (from-to)	603-611
Number of pages	9
Journal	International Journal of Systems Science
Volume	25
Issue number	3
DOIs	https://doi.org/10.1080/00207729408928983
Publication status	Published - Mar 1994
Externally published	Yes

ASJC Scopus subject areas

Control and Systems Engineering
Theoretical Computer Science
Computer Science Applications

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10.1080/00207729408928983

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abstract = "The problem of nonlinearity detection in system identification is treated. A probabilistic approach is taken which facilitates the analysis and enables the treatment of both strong and weak nonlinearities. The analysis shows that third- and fourth-order cumulants of the system output can be used to detect the existence of system nonlinearities, and to characterize their type",

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year = "1994",

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AU - Emara-Shabaik, H. E.

AU - Moustafa, K. A.F.

PY - 1994/3

Y1 - 1994/3

N2 - The problem of nonlinearity detection in system identification is treated. A probabilistic approach is taken which facilitates the analysis and enables the treatment of both strong and weak nonlinearities. The analysis shows that third- and fourth-order cumulants of the system output can be used to detect the existence of system nonlinearities, and to characterize their type

AB - The problem of nonlinearity detection in system identification is treated. A probabilistic approach is taken which facilitates the analysis and enables the treatment of both strong and weak nonlinearities. The analysis shows that third- and fourth-order cumulants of the system output can be used to detect the existence of system nonlinearities, and to characterize their type

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UR - https://www.scopus.com/pages/publications/0011778091#tab=citedBy

U2 - 10.1080/00207729408928983

DO - 10.1080/00207729408928983

M3 - Article

AN - SCOPUS:0011778091

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SP - 603

EP - 611

JO - International Journal of Systems Science

JF - International Journal of Systems Science

IS - 3

ER -

Characterization of dynamic system nonlinearities via probabilistic approach

Abstract

ASJC Scopus subject areas

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