Summary
In this work, we delve into the realm of time-frequency analysis techniques, with a particular emphasis on their application to nonlinear signals commonly encountered in various scientific and engineering domains. These signals, often exhibiting non-stationary and nonlinear characteristics, are crucial in the study of chaotic dynamics. Our focus is on the MultiSynchrosqueezing Transform (MSST), a emergent method for capturing the intricate structures and evolving features of these complex signals. Time-frequency analysis techniques, including MSST, are instrumental in examining the evolving characteristics of nonlinear signals. We begin by exploring a wide array of dynamical systems, setting the stage for a deeper understanding of their nonlinear behaviors. Classical methods like the Short-Time Fourier Transform, Wavelet Transform, Hilbert Transform, and the Wigner-Ville distribution have been extensively employed in analyzing non-stationary phenomena. Alongside MSST, our study highlights the enhanced capability of MSST in characterizing the unique aspects of chaotic and nonlinear dynamics.
