Stochastic resonance as a tool for smoothing time-frequency ridges in nonstationary signals

This study uncovers a novel role of stochastic resonance in enhancing the smoothness of time-frequency ridges in nonstationary signals. Such signals, characterized by rapidly varying frequencies and amplitudes, often exhibit irregular energy distributions. Environmental noise and component overlap further compromise the continuity of the time-frequency ridge. To address these challenges, this study proposes a bistable stochastic resonance system within an adaptive time-variable scale framework. Moreover, two new evaluation metrics—the continuity index and the smoothness index—are introduced to quantitatively assess the effectiveness of signal processing results. Simulation results demonstrate that the proposed method significantly improves the smoothness of time-frequency ridges, thereby facilitating a more accurate analysis of nonstationary signal characteristics. This framework offers a novel paradigm for time-frequency analysis in the context of complex, nonstationary signals.