Two Identification Methods for a Nonlinear Membership Function | Zendy

Yuejiang Ji | Zendy; Lixin Lv | Zendy

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Two Identification Methods for a Nonlinear Membership Function

Author(s) -

Yuejiang Ji,

Lixin Lv

Publication year - 2021

Publication title -

complexity

Language(s) - English

Resource type - Journals

SCImago Journal Rank - 0.447

H-Index - 61

eISSN - 1099-0526

pISSN - 1076-2787

DOI - 10.1155/2021/5515888

Subject(s) - nonlinear system , identification (biology) , function (biology) , mathematical optimization , mathematics , computer science , iterative method , algorithm , gradient method , botany , physics , quantum mechanics , evolutionary biology , biology

This paper proposes two parameter identification methods for a nonlinear membership function. An equation converted method is introduced to turn the nonlinear function into a concise model. Then a stochastic gradient algorithm and a gradient-based iterative algorithm are provided to estimate the unknown parameters of the nonlinear function. The numerical example shows that the proposed algorithms are effective.

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