Analysis of Adaptive Synchrosqueezing Transform with a Time-varying Parameter

TL;DR

This paper provides a theoretical analysis and error bounds for the adaptive Synchrosqueezing Transform, enhancing understanding of its effectiveness in separating non-stationary multicomponent signals.

Contribution

It offers the first theoretical error bounds for the adaptive WSST, validating its use in non-stationary signal separation.

Findings

Derived error bounds for component recovery

Validated the effectiveness of adaptive WSST through theoretical guarantees

Extended analysis to second-order adaptive WSST

Abstract

The synchrosqueezing transform (SST) was developed recently to separate the components of non-stationary multicomponent signals. The continuous wavelet transform-based SST (WSST) reassigns the scale variable of the continuous wavelet transform of a signal to the frequency variable and sharpens the time-frequency representation. The WSST with a time-varying parameter, called the adaptive WSST, was introduced very recently in the paper "Adaptive synchrosqueezing transform with a time-varying parameter for non-stationary signal separation". The well-separated conditions of non-stationary multicomponent signals with the adaptive WSST and a method to select the time-varying parameter were proposed in that paper. In addition, simulation experiments in that paper show that the adaptive WSST is very promising in estimating the instantaneous frequency of a multicomponent signal, and in accurate component recovery. However the theoretical analysis of the adaptive WSST has not been studied. In this paper, we carry out such analysis and obtain error bounds for component recovery with the adaptive WSST and the 2nd-order adaptive WSST. These results provide a mathematical guarantee to non-stationary multicomponent signal separation with the adaptive WSST.