2017 Volume 30 Issue 8 Pages 323-329
A new algorithm is proposed to estimate parameters of SISO (Single-Input Single-Output) system. The algorithm is an expansion of the previously proposed algorithms by the author with iterative estimation of the variances of noises. The previously proposed algorithms are based on the assumption that input and output noises have no correlation. Whereas, the method proposed in this paper is available even if input and output noises have correlation. This algorithm uses an iterative calculation and it consists of two parts. One part is the estimation of the system parameters by use of the variance and covariance matrix of input and output noises. The estimation of the system parameters is one of the least squares identification algorithms using eigenvector. The other part is the estimation of the variances and covariances of input and output noises using the system parameters. The variances and covariance of noises are estimated by solving linear simultaneous equations derived from the system parameters of transfer functions. The simulation results show the effectiveness of the proposed method.