Parametric Modeling of Non-Stationary Signals

TL;DR

This paper introduces parametric models tailored for non-stationary signals like speech and ECG, along with methods for precise parameter estimation, enhancing analysis of transient and dynamic signals.

Contribution

It presents new feature-based parametric models and estimation techniques specifically designed for non-stationary signals such as speech and biomedical signals.

Findings

Models effectively fit transient signals

Parameter estimation methods improve accuracy

Applicable to speech, ECG, and other non-stationary signals

Abstract

Parametric modeling of non-stationary signals is addressed in this article. We present several models based on the characteristic features of the modeled signal, together with the methods for accurate estimation of model parameters. Non-stationary signals, viz. transient system response, speech phonemes, and electrocardiograph signal are fitted by these feature-based models.