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, new principle signals in time and frequency domains explored. Secondly, an two obtained. They show that lower bounds are related to covariance can be achieved by chirp with Gaussian Then conditional standard deviations spectrogram associated derived. addition, example also carried out verify correctness theoretical analyses. Finally, potential applications presented effectiveness theorems.