Evaluation of the modified S-transform for time-frequency synchrony analysis and source localisation

Abstract

This article considers the problem of phase synchrony and coherence analysis using a modified version of the Stransform, referred to here as the Modified S-transform (MST). This is a novel and important time-frequency approach to study the phase coupling between two or more different spatially recorded entities with nonstationary characteristics. The basic method includes a cross-spectral analysis to study the phase synchrony of nonstationary signals, and relies on some properties of the MST, such as phase preservation. We demonstrate the usefulness of the technique using simulated examples and real newborn EEG data. The results show the advantage of using the cross-MST in the study of the connectivity between different signals using the time-frequency coherence. The MST led to improvements in resolution of almost twofold over the standard S-Transform in the examples presented in the article.

Time Frequency analysis of Non-Stationary signals by Differential frequency window S –Transform

“…5. It can be observed that proposed S-Transform (22) gives better localization when compared with Modified STransform [12].…”

“…4. It can be observed that small sign of indication for abrupt variation in proposed S-Transform (22) but it was not found in Modified S-Transform [12]. ii) Case at τ=1.054ms…”

“…The proposed algorithm is evaluated with other TFRs. Under normal environment conditions proposed algorithm TFR is equivalent to modified S-Transform [12]. But the proposed algorithm gives improved results in abrupt environment when compared with other TFRs.…”

“…In novel method of optimized frequency window proposed in [12,13], a new differential frequency window is proposed in this section. The major aim of this window is to track all abrupt amplitude-frequency variations which exist in non stationary signal.…”

“…Today in many of real time applications power spectral densities of signal are major requirement for signal analysis [11]. In such cases if the signal is contaminated by abrupt signal, ST suffers to provide time frequency analysis at faster rate due to lesser higher frequency localization [12] [13]. The following proposed method resolves spectral density components at higher rate with accuracy resolution.…”