A maximum likelihood estimator for linear and nonlinear systems-a practical application of estimation techniques in measurement problems

A method is presented for estimating the parameters of linear systems and nonlinear systems. The linear systems are modeled by their transfer function, while the nonlinear systems are described by a Volterra series. The estimator belongs to the class of maximum-likelihood estimators. During the estimation process, the Cramer-Rao lower bound on the covariance matrix of the estimates is derived.>