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[求助] 请信号处理高手翻译一下关于S变换和TT变换的英文，谢谢！

1、A novel technique of analysis of an arbitrary primary time series into a set of secondary, timelimited,local, constituent time series, the TT-transform, is presented. The time–time representation is derived from the S-transform, a method of representation of a real time series as a set of complex,
time-localized spectra.When integrated over time, the S-transform becomes the Fourier transform of the primary time series. Similarly, when summed over the primary time variable, the TT-transform reverts to the primary time series. The invertibility of the TT-transform points to the possibility of filtering and signal to noise improvements in the time domain, and some insight into the localized
spectra of the S-transform.
2、we present a two-dimensional time–time representation of a onedimensional
time series, based upon the S-transform. This is termed the TT-transform.
One of the major utilities of the TT-transform is the time-local view, through the scaled windows, of the primary time series. This aids in the interpretation of the S-transform. In fact, we recommend that the S-transform and TT-transform be always looked at as a side by side pair, thus avoiding interpreting artifacts as real information and vice versa. Our experience suggests that similar procedures be followed for all spot transform techniques, such as wavelet transforms.
3、In this paper we have presented the TT-transform, a new view of localizing the time features of a time series around a particular point on the time axis. The TT-transform is derived from the S-transform [4] and differs from windowed time series in that (as in the S-transform) the degree of localization of signal components is frequency dependent rather than frequency invariant. When examined along with the S-transform, the TT-transform provides a better understanding of the time-local properties of the time series than the
S-transform alone. In some instances it may also clarify the nature of artifacts introduced into the S-transform by the windowing process. The TT-transform has potential use in any applications which involve localization of different frequency components of a signal. The method can also be extended to produce a two-dimensional TT-transform [12], or localized image, derived using the two-dimensional S-transform [13,14].

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