The aim of the present paper is to propose an alternative technique based on the fuzzy methodology to investigate the dimensional complexity of biomedical signals generated by BCI. The signal identification is based on vectorial multifractal analyse that is mathematically formalized by the spectrum singularities of Hölder exponents evaluated on the interval [$0, \boldsymbol{T}$]. A fuzzy technique is used to calculate the Hölder exponents of the signal. The Husdorff parameters are evaluated by several techniques: averaging, norm, Center of Gravity Method and spectral estimation. A Type-2 Fuzzy Set method is used to classificate and sorte the signals. Numerical results of the propsed techniques are discussed.
[1]
Yuan Yan Tang,et al.
A Fractal Dimension and Wavelet Transform Based Method for Protein Sequence Similarity Analysis
,
2015,
IEEE/ACM Transactions on Computational Biology and Bioinformatics.
[2]
Andrew A Fingelkurts,et al.
Natural world physical, brain operational, and mind phenomenal space-time.
,
2010,
Physics of life reviews.
[3]
Alexei Sourin,et al.
Human electroencephalograms seen as fractal time series: Mathematical analysis and visualization
,
2006,
Comput. Biol. Medicine.
[4]
A. Karcı.
The Physical and Geometrical Interpretation of Fractional Order Derivatives
,
2015
.