Uncertainty principles for the short-time linear canonical transform of complex signals

The short-time linear canonical transform (STLCT) is a novel time-frequency analysis tool. In this paper, we generalize some different uncertainty principles for the STLCT of complex signals. Firstly, a new uncertainty principle for STLCT of complex signals in time and frequency domains is explored. Secondly, an uncertainty principle in two STLCT domains is obtained. They show that the lower bounds are related to the covariance of time and frequency and can be achieved by complex chirp signals with Gaussian signals. Then the uncertainty principle for the two conditional standard deviations of the spectrogram associated with the STLCT is derived. In addition, an example is also carried out to verify the correctness of the theoretical analyses. Finally, some potential applications are presented to show the effectiveness of the theorems.