摩尔-彭罗斯伪逆
趋同(经济学)
人工神经网络
模糊逻辑
秩(图论)
基质(化学分析)
计算机科学
数学
控制理论(社会学)
人工智能
反向
组合数学
控制(管理)
材料科学
经济
复合材料
经济增长
几何学
作者
Vasilios N. Katsikis,Predrag S. Stanimirović,Spyridon D. Mourtas,Lin Xiao,Darjan Karabašević,Dragiša Stanujkić
出处
期刊:IEEE Transactions on Fuzzy Systems
[Institute of Electrical and Electronics Engineers]
日期:2022-09-01
卷期号:30 (9): 3426-3435
被引量:39
标识
DOI:10.1109/tfuzz.2021.3115969
摘要
A correlation between fuzzy logic systems (FLS) and zeroing neural networks (ZNN) design is investigated. It is shown that the gain parameter included in ZNN design can be dynamically adjusted over time by means of an appropriate value derived as the output of a properly defined FLS, which includes appropriately defined membership functions and fuzzy logic rules. Dynamical systems which are applicable to time-varying rank-deficient matrices are proposed. Convergence properties are investigated and illustrative simulation experiments are performed. Presented simulation experiments confirm the superiority of the FLS proposed in this article with respect to previously proposed FLS for dynamic adjustment of gain parameters. Furthermore, the superiority of the FLS-based ZNN model over the corresponding ZNN models based on the classical approach in defining the varying-gain parameter is demonstrated.
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