Two Identification Methods for a Nonlinear Membership Function. (3rd May 2021) - Ji, Yuejiang; Lv, Lixin
Abstract : 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.