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A Hankel matrix approach to stochastic model reduction

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2 Author(s)
B. Bacon ; Purdue University, West Lafayette, IN, USA ; A. Frazho

A procedure for stochastic model reduction is Presented utilizing the Hankel matrix results of Adamjan, Arov, and Krein in a way not previously exploited. It is shown thai the error variance of the resulting N th-order approximation is bounded from above by the N + 1 singular value of the system's Hankel matrix.

Published in:

IEEE Transactions on Automatic Control  (Volume:30 ,  Issue: 11 )