On identification of parallel block-cascade nonlinear models

Hosam E. Emara-Shabaik, Kamal A.F. Moustafa, Jaleel H.S. Talaq

Research output: Contribution to journalArticlepeer-review

9 Citations (Scopus)


The class of nonlinear systems studied in this paper is assumed to be modelled by parallel block-cascades. Such models are composed of parallel branches where each branch has a linear block in cascade with a zero-memory nonlinear block followed by another linear block. These types of models are extensively used to represent nonlinear dynamic systems and are known in the literature as Wiener-Hammerstein models. Using a zero-mean stationary white gaussian sequence as an input to such models, a structure identification criterion is developed, utilizing the bispectrum estimate of the output sequence only. The application of this criterion is shown by several simulation examples. Also, impulse response estimation of an example of such a model is considered to show the effectiveness of the proposed identification technique.

Original languageEnglish
Pages (from-to)1429-1438
Number of pages10
JournalInternational Journal of Systems Science
Issue number7
Publication statusPublished - Jul 1995
Externally publishedYes

ASJC Scopus subject areas

  • Control and Systems Engineering
  • Theoretical Computer Science
  • Computer Science Applications


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