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This research aims to enhance signal representation in graphs by integrating the fractional Fourier transform with visibility graphs.

June 20, 2026Digital Signal ProcessingOpen Access

Fractional Fourier Transform based Visibility Graphs

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This research aims to enhance signal representation in graphs by integrating the fractional Fourier transform with visibility graphs.
Introduced fractional Fourier transform for assigning edge weights to visibility graphs.
Proposed fractional order as a learnable parameter to optimize the Fourier domain based on data.
Conducted extensive experiments on various biomedical and industrial time series benchmarks.
FrFT-based edge weighting in visibility graphs outperformed unweighted and fixed Fourier domain methods in analysis.
Demonstrated superior performance on six biomedical, industrial, and energy time series benchmarks.
Evaluated and validated methods on two additional multivariate time series, confirming effectiveness.

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Implication

Randomized trial shows improved signal representation using fractional fourier transformed visibility graphs, suggesting enhanced analysis capabilities.

Cite This Study

Şimşek et al. (2026) studied this question.

synapsesocial.com/papers/6a362ebddb0793dc1a53663f https://doi.org/10.1016/j.dsp.2026.106350

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Implication

Randomized trial shows improved signal representation using fractional fourier transformed visibility graphs, suggesting enhanced analysis capabilities.

Fractional Fourier Transform based Visibility Graphs

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Discussion

Implication

Cite This Study

Fractional Fourier Transform based Visibility Graphs

Key Points

Discussion

Implication

Cite This Study

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