数学形态学视角下的模糊联想记忆

M. E. Valle, P. Sussner
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引用次数: 14

摘要

数学形态学(MM)是一种利用基于拓扑和几何概念的算子处理和分析物体的理论。当模糊联想记忆(FAM)模型配备与数学形态学算子相对应的神经元时,我们称之为模糊形态学联想记忆(FMAM)。本文提出了几种FAM模型,包括Kosko的FAM模型、Chung和Lee的最广义FAM模型、Junbo等人的FAM模型、带阈值的最大最小FAM模型、模糊逻辑双向联想记忆模型和隐含模糊联想记忆模型,均属于FMAM类。此外,我们还提出了两种从给定的FMAM中导出新的FMAM模型的策略。这些策略是基于数学形态学的两种对偶关系:关于否定的对偶和关于附加的对偶。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Fuzzy Associative Memories from the Perspective of Mathematical Morphology
Mathematical morphology (MM) is a theory concerned with the processing and analysis of objects using operators based on topological and geometrical concepts. We speak of a fuzzy morphological associative memory (FMAM) when a fuzzy associative memory (FAM) model is equipped with neurons that correspond to an operator of mathematical morphology. This paper shows that several FAM models, including the FAMs of Kosko, most generalized FAMs of Chung and Lee, the FAM of Junbo et al., the max-min FAM with threshold, the fuzzy logic bidirectional associative memories, and the implicative fuzzy associative memories, belong to the FMAM class. Moreover, we present two strategies for deriving a new FMAM model from a given FMAM. These strategies are based on two duality relationship of mathematical morphology: duality with respect to negation and duality with respect to adjunction.
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