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Image processing: the nature and value of fuzzy metrology

机译:图像处理:模糊度量的性质和价值

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The term "fuzzy metrology" is almost as misleading as the term "fuzzy logic." Many people simply avert their eyes from fuzzy logic, because they know (correctly) that good logic is not fuzzy but rigorous. But, neither the measured result nor the logic itself is fuzzy in any conventional sense. Many sets are fuzzy, so they must be handled not by crisp logic but by fuzzy logic. Fuzzy logic itself is quite rigorous. Likewise, fuzzy metrology uses the mechanisms of fuzzy logic to arrive at precise measurements of physical things. In itself it is rigorous. You avert your eyes at your peril. After a general discussion of the basics of fuzzy logic, I show a number of examples that allow the user even better understanding of when fuzzy metrology might be superior to conventional crisp metrology.
机译:术语“模糊计量”几乎与术语“模糊逻辑”一样具有误导性。许多人只是避开模糊逻辑,因为他们(正确地)知道好的逻辑不是模糊的而是严格的。但是,从任何常规意义上讲,测量结果或逻辑本身都不是模糊的。许多集合是模糊的,因此必须不使用清晰逻辑来处理它们,而应使用模糊逻辑来处理它们。模糊逻辑本身非常严格。同样,模糊计量学也使用模糊逻辑机制来对物理事物进行精确测量。它本身是严格的。您避免视而不见。在对模糊逻辑基础进行了一般性讨论之后,我展示了许多示例,这些示例使用户可以更好地了解何时模糊度量可能优于传统的清晰度量。

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