Comparison of conventional methods and the ISD-IST shows that the ISD (ISD-IWT and ISD-IST) methods have higher resolution and accuracy and can provide more reliable time-frequency phase spectra, and it further verifies the greater continuity and stability of ISD-IST over ISD-IWT. In this paper, we have extended ISD into other linear transforms and have developed an ISD based on inverse S transform (ISD-IST), which has higher continuity and stability due to the more adjustable and adaptable mother wavelet of the S transform. However, the traditional inverse spectral decomposition (ISD) algorithm is based on an inverse wavelet transform (IWT) whose mother wavelet is a Ricker wavelet function instead of an adaptive wavelet, which causes poor continuity and instability of the ISD results. Spectral decomposition based on sparse constrained inversion, as proposed in recent years, is a high-resolution time-frequency domain analysis method.
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