H Model Reduction of 2-D Discrete Systems

Part of the Lecture Notes in Control and Information Sciences book series (LNCIS, volume 278)


The problem of model reduction for 2-D systems has received considerable attention due to their importance in 2-D signal and image processing applications [61][65][99][100] where it is usually desirable to represent a high-order system by a lower-order model. The essence of model reduction is to obtain a reduced order model which approximates the original system without significant error. Recently, the H model reduction method has attracted a lot of interest for 1-D systems; see [38][55][56]. The H model reduction aims to find a low-order model such that the H norm of the difference between the original model and the reduced order model is small.


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© Springer-Verlag Berlin Heidelberg 2002

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