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.

中文翻译：

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非线性隶属度函数的两种辨识方法

针对非线性隶属度函数，提出了两种参数辨识方法。引入了方程转换方法，将非线性函数转换为简洁的模型。然后提供了一种随机梯度算法和一种基于梯度的迭代算法来估计非线性函数的未知参数。数值算例表明，所提算法是有效的。