The Synchroextracting Transform (SET) is a novel and powerful time-frequency analysis technique designed to overcome the resolution limitation imposed by the Heisenberg uncertainty principle in traditional methods. Unlike conventional approaches that retain the entire time-frequency spectrum, SET employs a synchroextracting operator to identify and preserve only the most energy-concentrated time-frequency coefficients associated with the signal's instantaneous frequency. This process effectively filters out smeared and diffused energy, resulting in a highly sparse and sharpened time-frequency representation. This paper elaborates on the fundamental principle of SET and validates its performance using synthetic non-stationary signals. The results demonstrate that SET achieves superior energy concentration and provides exceptional resolution in distinguishing signal components that are otherwise blurred in Short-Time Fourier Transform (STFT) and S-Transform analyses. The method shows significant potential for high-precision signal characterization in various engineering and geophysical applications.