Arma Parameter Estimation Using Continuation Methods
This paper proposes and provides initial investigations into new homoropy-based algorithms for solving the nonlinear auto-regressive-moving-average (ARMA) parameter estimation problem. Nonlinear defining equations for the optimal system parameters result in a multi-modal performance suiIiice. Current numerical methods for solving these nonlinear ARMA estimation problems use gradient-based numerical methods, which cannot distinguish between local and global minima, solve related suboptimal problems, or may not converge. Homoropy-based continuation methods are globally-convergent numerical methods from which algorithms for finding the global minimum of these nonlinear ARMA estimation problems can be formed.