Parametric modeling and application of systems with impulse effect

Systems with impulse effect are widely used as a practical mathematical modeling tool for systems and processes, which undergo rapid change. In this paper, the authors employ systems with impulse effect in combination with the conventional auto-regressive moving-average model to successfully estimate the parameters of a non-Gaussian signal inhibited by a specific type of non-Gaussian noise. The additive noise process being examined contains sharp spikes. An inference is made about the effectiveness and limitation of the proposed parametric modeling approach