Adaptive deconvolution based on spectral decomposition

摘要

Abstract: An adaptive algorithm for estimating the input to a linear system is presented. This explicit self-tuning filter is based on the identification of an innovations model. From that model, input and measurement noise ARMA-descriptions are decomposed, using second order moments. Identifiability results guarantee a unique decomposition. Main tools in the algorithm are the solution of two linear systems of equations. The filter design is based on the polynomial approach to Wiener filtering. !18