System Maintenance Notice:
Single article purchases and IEEE account management are currently unavailable. We apologize for the inconvenience.
By Topic

On the robust estimation of the autocorrelation coefficients of stationary sequences

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

The purchase and pricing options are temporarily unavailable. Please try again later.
2 Author(s)
Batalama, S.N. ; Dept. of Electr. & Comput. Eng., State Univ. of New York, Buffalo, NY, USA ; Kazakos, D.

This paper discusses methods for the estimation of the autocorrelation coefficients of a finite-dependent stationary random sequence. Three estimators are examined: the sample average and two proposed approaches, namely the pseudo-maximum-likelihood (pseudo-ML) estimator and the pseudo-M estimator. The latter scheme is found as a solution of a Fredholm integral equation. All three estimators are first studied for specific distribution models. Then the existence of a minimax robust design is proved and a suboptimally robust scheme is proposed. Simulation results illustrate the theoretical foundations of the methods and indicate that the pseudo-M estimator achieves significantly better performance than the other two schemes when tested against dependent data and in the presence of outliers. Finally, the results may also be applied to the estimation of a location parameter of a dependent random sequence

Published in:

Signal Processing, IEEE Transactions on  (Volume:44 ,  Issue: 10 )