Abstract
This paper proposes a robust identification method for an ARX model using Beta divergence. The proposed method is derived by minimizing Beta divergence, which measures the difference between a true and estimated probability distribution. The iteration law of the proposed method is the special case of a weighted least squares method. A numerical simulation demonstrates the effectiveness of the proposed method.
