Field of Research: Electric Engineering
Name of author) (s): Ahmed Abdou, Flavius Turcu, Eric Grivel, Roberto Diversi and Guillaume Ferré
Title of published work: “Identifying an autoregressive process disturbed by a moving-average noise using inner–outer factorization”
Name of Journal: Signal, Image and Video Processing
This paper deals with the identification of an autoregressive (AR) process disturbed by an additive moving-average (MA) noise. Our approach operates as follows: Firstly, the AR parameters are estimated by using the overdetermined high-order Yule–Walker equations. The variance of the AR process driving process can be deduced by means of an orthogonal projection between two types of estimates of AR process correlation vectors. Then, the correlation sequence of the MA noise is estimated. Secondly, the MA parameters are obtained by using inner–outer factorization. To study the relevance of the resulting method, we compare it with existing algorithms, and we analyze the identifiability limits. The identification approach is then combined with Kalman filtering for channel estimation in mobile communication systems.
Autoregressive process (AR) Moving-avergae process (MA) Inner–outer factorization Overdetermined high-order Yule–Walker equations Contact info of the contact author (s):
Name: Ahmed Abdou, PhD.
Address: Department of Electronic and Communication Engineering, Al-Quds University