广义模糊散度测度、模式识别和不等式

R. Saraswat, Neha Khatod
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引用次数: 1

摘要

许多研究者和作者开发的模糊信息和散度度量。本文利用凸函数的性质和模糊概念,提出了一种新的模糊散度测度方法。通过实例讨论了新型模糊发散测度在模式识别中的应用。在模糊散度测度上得到了各种新的模糊信息不等式。利用新的f-散度、Jensen不等式、凸函数的性质和不等式,研究了新的和现有的模糊散度测度之间的新关系。最后通过数值算例验证了这些结果,并提出了模糊散度度量方法。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Generalized Fuzzy Divergence Measure, Pattern Recognition, and Inequalities
Many fuzzy information and divergence measures developed by various researchers and authors. Here, authors proposed new fuzzy divergence measure using the properties of convex function and fuzzy concept. The applications of novel fuzzy divergence measures in pattern recognition with case study, are discussed. Obtained various novel fuzzy information inequalities on fuzzy divergence measures. The new relations among new and existing fuzzy divergence measure by new f-divergence, Jensen inequalities, properties of convex functions and inequalities have studied. Finally, verified these results and proposed fuzzy divergence measures by numerical example.
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