Passivity Based Performance in Interfered Digital Filters

Abstract

This research aims to mitigate the impact of memory effects, interference, and saturation nonlinearities in digital filters through a rigorous methodology. By introducing external perturbations and threshold constraints, a novel stability criterion based on the Hankel model is proposed for digital filters. This criterion assesses the uncertainty in previously observed filter behaviors. Additionally, a stability analysis method ensures asymptotic stability in the absence of external signals. Numerical examples illustrate the effectiveness of the proposed techniques, demonstrating improved performance under challenging operational conditions.