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- fuzzy entropy triple I method 模糊熵三I算法
- Triple I method is a new kind fuzzy reasoning method with respect to FMP and FMT reasoning models. 三I算法是针对模糊推理的FMP与FMT模型的一种新的推理方法。
- Triple I method is a new fuzzy reasoning method with respect to FMP and FMT reasoning models. 摘要三I算法是针对模糊推理FMP与FMT模型的一种新的推理方法。
- fuzzy entropy reverse triple I algorithm 模糊熵反向三I算法
- First, the notion of fake residue pair is introduced and the united forms of FMP Triple I method based a sort of implication operator or implication operators with parameter is given. 摘要首先提出了伪伴随对的概念，基于此给出了基于一类蕴涵算子或带参数的蕴涵算子的FMP三I算法的统一形式；
- A Fuzzy Reasoning Model of Characteristic Expansion Based on Triple I Method and Its Application in Expert System 特征展开三I Fuzzy推理模型及其在专家系统中的应用
- fuzzy entropy s-reverse triple Ⅰ method 模糊熵α-反向三Ⅰ算法
- Sheng K W, Zheng J H.A new method for gray-level picture thresholding using the fuzzy entropy[J].Signal Processing, 1998, 14(3): 269-272 . [8]生克伟;郑建宏.;一种新的模糊熵图象分割方法[J]
- A method of multi-level image restoration based on fuzzy entropy is presented. The method can extend the entropy's express form in terms of entropy's limitations on application. 提出了一种基于模糊熵的多值图像恢复方法,该方法根据在应用方面的局限性对其表示的形式进行了扩展。
- Abstract: A method of image threshold based on a convex polynomial fuzzy entropy is proposed by replacing Shannon's function of fuzzy entropy with a convex polynomial. 文摘:采用一种凸多项式代替模糊熵中的香农函数，提出了基于凸多项式模糊熵的图象阈值方法。
- The final CFV for hypothesis is given based on mean and fuzzy entropy of all CFV. 一个假设可信度值CFV的最终值是根据各可信度值的平均值和模糊熵来确定的.
- Reverse triple I method 反向三I算法
- Before adopting a fuzzy entropy similarity metric, edge detection, image segmentation and segmentation description are accomplished. 针对两幅不同时相图像,该方法先进行区域特征提取,然后通过构造模糊熵差匹配度量函数来实现图像的自动匹配。
- triple I method 三I算法
- Dual Form of Triple I Method 对偶三I算法
- restricted triple I method 三Ⅰ约束算法
- b-quasi conditional fuzzy entropy b-拟条件模糊熵
- two-dimensional fuzzy entropy principle 二维时空模糊熵准则
- maximum fuzzy entropy Gaussian clustering 最大模糊熵高斯聚类
- How can I persuade you of my sincerity? 我如何能够让你相信我的诚意？
