شماره ركورد كنفرانس :
3208
عنوان مقاله :
A New Kalman Filter Based 2-D AR Model Parameter Estimation Method
پديدآورندگان :
Zeinali, Mahdi Department of electrical engineering - Sahand University of Technology , Shafiee, Masoud Department of electrical engineering - Amirkabir University of Technology , Nosrati, Komeil Department of electrical engineering - Amirkabir University of Technology
كليدواژه :
Two dimensional , time series , parameter estimation , autoregressive model , Kalman filter , identification
عنوان كنفرانس :
چهارمين كنفرانس بين المللي كنترل، ابزار دقيق و اتوماسيون
چكيده لاتين :
This paper presents a new method for the causal
quarter-plane (QP) region of support two dimensional (2-D)
autoregressive model parameters estimation based on the
Kalman filter (KF). To achieve this aim, the corresponding
relations are extended to the 2-D case and the related algorithm
is presented. Online parameter estimation, capability of
parameters variation detection, estimation improvement by using
new data and less computational requirement are the significant
advantages of the proposed method. As a result of not involving
complex and time consuming matrix computations, the presented
method is computationally efficient. Numerical simulation is
presented to show the efficiency of the proposed approach.
