Adaptive deconvolution based on spectral decomposition

Anders Ahlen; Mikael Sternad

doi:10.1117/12.49771

1 December 1991 Adaptive deconvolution based on spectral decomposition

Anders Ahlen, Mikael Sternad

Proceedings Volume 1565, Adaptive Signal Processing; (1991) https://doi.org/10.1117/12.49771
Event: San Diego, '91, 1991, San Diego, CA, United States

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.

Citation Download Citation

Anders Ahlen and Mikael Sternad "Adaptive deconvolution based on spectral decomposition", Proc. SPIE 1565, Adaptive Signal Processing, (1 December 1991); https://doi.org/10.1117/12.49771

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