The windowed Fourier transform (short time Fourier transform) and the S-transform are widely used signal processing tools for extracting frequency information from non-stationary signals. Previously, the windowed Fourier transform had been adopted for signals on graphs and has been shown to be very useful for extracting vertex-frequency information from graphs. However, high computational complexity makes these algorithms impractical. We sought to develop a fast windowed graph Fourier transform and a fast graph S-transform requiring significantly shorter computation time. The proposed schemes have been tested with synthetic test graph signals and real graph signals derived from electroencephalography recordings made during swallowing. The results showed that the proposed schemes provide significantly lower computation time in comparison with the standard windowed graph Fourier transform and the fast graph S-transform. Also, the results showed that noise has no effect on the results of the algorithm for the fast windowed graph Fourier transform or on the graph S-transform. Finally, we showed that graphs can be reconstructed from the vertex-frequency representations obtained with the proposed algorithms. (C) 2016 Elsevier B.V. All rights reserved.
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Foshan Univ, Sch Math & Big Data, Foshan 528000, Peoples R ChinaFoshan Univ, Sch Math & Big Data, Foshan 528000, Peoples R China
Zheng, Xianwei
Zou, Cuiming
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Huazhong Agr Univ, Coll Sci, Wuhan 430070, Peoples R ChinaFoshan Univ, Sch Math & Big Data, Foshan 528000, Peoples R China
Zou, Cuiming
Dong, Li
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Ningbo Univ, Dept Comp Sci, Ningbo, Zhejiang, Peoples R ChinaFoshan Univ, Sch Math & Big Data, Foshan 528000, Peoples R China
Dong, Li
Zhou, Jiantao
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Univ Macau, State Key Lab Internet Things Smart City, Macau, Peoples R China
Univ Macau, Dept Comp & Informat Sci, Macau, Peoples R ChinaFoshan Univ, Sch Math & Big Data, Foshan 528000, Peoples R China