Abstract
As a generalization of classical Fourier transformation (FT), the fractional Fourier transform (FrFT) outperforms many other time frequency analysis techniques with its higher time-frequency resolution, but it is quite new to be employed into the biomedical signal processing. In this paper, the FrFT has been investigated for the application of biomedical signal detection, which shows to be effective to nonstationary weak signal detection in additive white Gaussian noise (AWGN). The second-order fractional FT moments and estimation are used for the multi-component chirps and interference situation. The results indicate the great advantage on biomedical signal detection by FrFT.
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