An appropriate membership function is defined to express the distribution of image samples.

通过分析图像样本的分布特点,定义合适的隶属度函数描述图像空间的样本分布.

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A reasonable method is presented for establishing membership function and enlarging the feasible domain.

提出了较为完善的构造隶属函数的方法,扩充了可行域.

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By analyzing the characteristic quantity and choosing relevant membership function, corresponding fuzzy mathematical model is given.

通过分析故障时的特征量,并选择合适的隶属函数, 建立了相应的模糊数学模型.

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Baldwin ? ? truth value restriction multiconditional fuzzy reasoning algorithms is presented in discrete membership function.

Baldwin的真值限定概念,给出了在离散隶属函数下的一组基于MAX-⊙ 复合运算和模糊关系Rb的多条件模糊真值推理算法.

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