Analysis of the ensemble of regression algorithms for the analog circuit parametric identification

摘要

The paper presents the application of the combined group of regression algorithms for the parameter identification of the analog circuit's state. The fusion of regression machines is a new approach aimed at obtaining the high accuracy in the diagnosis of parametric faults determined in the presence of noise. The ensemble consists of multiple approaches, mainly based on variants of the linear regression techniques. Because the methods are simple, it is easier to build the accurate module than for the typical heuristic approach, such as Support Vector Machines (SVM). The methodology consists in preparing the ensemble architecture, selecting computational methods, optimizing features extracted from the diagnosed system and testing the module. It was tested on the 5th order lowpass filter and compared with the single regression algorithm, treated as the reference method. Obtained results show the usefulness of the proposed framework for the accurate identification of analog system parameters. (C) 2020 The Author. Published by Elsevier Ltd.