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Towards the Defuzzification Procedure in an ANFIS

机译:走向ANFIS中的反模糊化程序

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The paper pays attention to particularities concerned with the defuzzification procedure in adaptive neural network based fuzzy inference systems. Specifically, the problem of constructing recursive parameter estimation algorithms is considered with regard to their convergence and stability. In the combination with various forms of the quadratic criterion, such an approach enables on to obtain strongly consistent estimation algorithms under essential generality of modeled system description; and the convergence properties are demonstrated in the comparison with conventional algorithms.
机译:本文注重基于自适应神经网络的模糊推理系统中的Defuzzzification程序的特殊性。具体地,考虑了构建递归参数估计算法的问题,考虑到它们的收敛和稳定性。在与各种形式的二次标准的组合中,这种方法能够在建模系统描述的基本一般性下获得强烈一致的估计算法;在与传统算法的比较中对收敛性进行说明。

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