A Review and Genetic Algorithm-Based Adaptive Window Optimization of the Stockwell Transform

This article examines the evolution of the Stockwell Transform (ST) over the years and proposes a new optimization method, called the Genetic Algorithm Optimization Approach (GAOA), designed to improve the analysis of complex signals by adjusting the standard deviation of the window function according to their characteristics. For example, this is of interest in case of electric signals, e.g., when targeting to ensure electrical power quality. At first, the present paper reviews the different variants of the ST that exist in the literature, addressing the generalized versions as well as the optimized ones and their applications in different fields. After addressing their advantages and limitations, we present the proposed GAOA, which addresses an adaptation of the signals’ standard deviation of the window function to optimize time and frequency resolution. The comparison with other variants of the ST highlights the potential advantages of GAOA for more accurate analysis of complex signals.