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An Extended Algorithm of Similarity Measures and Its Application to Radar Target Recognition Based on Intuitionistic Fuzzy Sets

机译:基于直觉模糊集的相似性度量扩展算法及其在雷达目标识别中的应用

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The main purpose of this study was to extend an algorithm proposed by Liang and Shi in 2003 for the measurement of similarity in pattern-recognition problems. The third measure of similarity in their algorithm fails to satisfy the necessary criteria, thereby invalidating their claims. In this study we developed two new approaches that satisfy the four axioms associated with the measurement of similarity. We then implemented these measures in a new algorithm and used numerical examples to examine the problem encountered by Liang and Shi. Finally, we evaluated the applicability of the proposed algorithm in a problem involving radar target recognition. Our findings provide a solid foundation for the development of a logical framework with which to select an appropriate measure of similarity for pattern-recognition problems.
机译:这项研究的主要目的是扩展由Liang和Shi于2003年提出的一种用于测量模式识别问题中相似度的算法。他们算法中相似性的第三种衡量标准无法满足必要标准,从而使他们的主张无效。在这项研究中,我们开发了两种新方法,可以满足与相似性度量相关的四个公理。然后,我们在新算法中实现了这些度量,并使用数值示例来检验Liang和Shi遇到的问题。最后,我们评估了该算法在涉及雷达目标识别的问题中的适用性。我们的发现为逻辑框架的发展提供了坚实的基础,通过该逻辑框架可以为模式识别问题选择适当的相似性度量。

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