Estimation of Delay Time in Linear Dynamic Systems Using Wavelets

 This research explores the use of wavelets in estimating delay time in stochastic linear dynamic systems, as delay time plays a crucial role in diagnosing the system by determining the time interval between inputs and outputs. Several simulation experiments were conducted, utilizing one type of wavelet—the Haar wavelet—for data processing. Subsequently, various methods for estimating delay time were applied, and the results were compared. The findings indicate that estimating delay time using the Haar wavelet yielded better results when applied to an autoregressive model with additional inputs compared to the unprocessed data. The research aims to employ the har wavelet in the process of estimating the delay time in stochastic linear dynamic models using some estimation methods and comparing the results based on simulation experiments