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Signal Processing Using Fuzzy Fractal Dimension and Grade of Fractality -Application to Fluctuations in Seawater Temperature

机译:模糊分形维数和分形等级的信号处理-在海水温度波动中的应用

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Discrete signal processing using fuzzy fractal dimension and grade of fractality is proposed based on the novel concept of merging fuzzy theory and fractal theory. The fuzzy concept of fractality, or self-similarity, in discrete time series can be reconstructed as a fuzzy-attribution, i.e., a kind of fuzzy set. The objective short time series can be interpreted as an objective vector, which can be used by a newly proposed membership function. Sliding measurement using the local fuzzy fractal dimension (LFFD) and the local grade of fractality (LGF) is proposed and applied to fluctuations in seawater temperature around the Izu peninsula of Japan. Several remarkable characteristics are revealed through "fuzzy signal processing" using LFFD and LGF
机译:在融合模糊理论和分形理论的新概念的基础上,提出了基于模糊分形维数和分形等级的离散信号处理方法。离散时间序列中的分形性或自相似性的模糊概念可以重构为模糊属性,即一种模糊集。目标短时间序列可以解释为目标向量,可以由新提议的隶属函数使用。提出了使用局部模糊分形维数(LFFD)和局部分形度(LGF)进行滑动测量的方法,并将其应用于日本伊豆半岛附近海水温度的波动。通过使用LFFD和LGF的“模糊信号处理”揭示了几个显着特征

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