An Algorithm for Identification of Single-Input Single-Output Linear Systems with Estimation of Variance of Input-Output Noises

A new algorithm is proposed to estimate parameters of SISO system. The proposed method is applied to the errors-in-variables (EIV) models. The algorithm uses an iterative calculation and it consists of two parts. One part is the estimation of the system parameters using the variances of errors. The other part is the estimation of the variances of errors using the system parameters. The estimation of the system parameters is one of the least squares identification algorithms using eigenvector. The variances of errors is estimated by solving linear simultaneous equations derived from the difference equation of the system. An experimental result and some simulations show the effectiveness of the proposed method. The proposed method is simple and easy to be understood. Therefore, it is easy to adopt the proposed method in practical system.