A polynomial-algebraic method for non-stationary TARMA signal analysis

Time dependent AutoregRessive Moving Average (TARMA) models, with parameters belonging to a sub-space spanned by time-domain functions, offer appropriate representation for a fairly wide class of non-stationary signals. Yet, their estimation is difficult, due to problems related to local extrema and the need for accurate initial guess parameter values. In this paper a Polynomial-Algebraic (P-A) TARMA estimation method is introduced. The P-A method achieves low computational complexity while eliminating the need for initial guess parameter values and avoiding local extrema problems. Its performance is demonstrated via Monte Carlo simulations.