Estimating the model parameters of deep-level transient spectroscopy data using a combined wavelet/singular value decomposition Prony method

In this article, a combined wavelet/singular value decomposition-Prony method to estimate the time constants associated with deep-level transient spectroscopy data is presented. A filtering scheme based on wavelet denoising is used to provide a preprocessing technique that allows the singular value decomposition-Prony method to be applied to transient capacitance data to accurately estimate the associated time constants. Results for both simulated multiple exponential model data with additive white-Gaussian noise and real transient spectroscopy data are presented to illustrate the applicability of the presented technique. Furthermore, the concept of detecting multiple time constants is investigated and a statistical analysis is performed to address the constraints associated with the presented technique to achieve effective detection and estimation.