Recursiveestimation of linear systems’ parameters based on cumulant matching

The problem of the estimation of the parameters of linear systems from noisy inputoutput measurements is considered. A third-order cumulant matching recursive algorithm is developed. The algorithm provides unbiased estimates of theparameters for a wide class of correlated noise corrupting both the input and the output measurements. A Monte Carlo type of simulation shows the consistency and the superiority of the developed algorithm over the least-squares technique.