A comparison of parameter estimation algorithms for discrete systems

Abstract Nine digital algorithms—five linear least-squares type, two stochastic approximation and two hill climbing—for estimating the parameters of discrete systems have been compared when applied to a second-order system having a stochastic input and output. Results are tabulated on the performance of these algorithms in terms of the variance and bias of the resulting estimates and their computer storage requirements and speed.