Maximum Likelihood, Weighted Kalman And Subspace Linear Prediction Algorithms For System Identification

For the problem of estimating parameters of a linear system from its input and output sequences, we present iterative quadratic maximum likelihood (IQML), iterative quadratic weighted Kalman (IQWK), and noniterative subspace linear prediction (SLP) algorithms. The SLP algorithms are based on a novel subspace deconvolution of the output. In particular, a double total-least-squares (D-TLS) SLP algorithm is provided.