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

Author

Kamijo, Kenichi ; Yamanouchi, Akiko

Author_Institution

Graduate Sch. of Life Sci., Toyo Univ., Gunma

fYear

2007

fDate

1-5 April 2007

Firstpage

133

Lastpage

138

Abstract

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

Keywords

fractals; fuzzy set theory; geophysics computing; ocean temperature; seawater; signal processing; time series; discrete signal processing; discrete time series; fuzzy attribution; fuzzy fractal dimension; fuzzy set; fuzzy signal processing; membership function; seawater temperature fluctuation; self-similarity; sliding measurement; Biomedical signal processing; Computational intelligence; Fluctuations; Fractals; Fuzzy sets; Fuzzy systems; Merging; Ocean temperature; Sea measurements; Signal processing;

fLanguage

English

Publisher

ieee

Conference_Titel

Computational Intelligence in Image and Signal Processing, 2007. CIISP 2007. IEEE Symposium on

Conference_Location

Honolulu, HI

Print_ISBN

1-4244-0707-9

Type

conf

DOI

10.1109/CIISP.2007.369306

Filename

4221407