Journal article

On the Realization of 2-D Linear Systems With Recursively Computable Latent Variable Models

Ran Yang, Lorenzo Ntogramatzidis, Michael Cantoni

IEEE TRANSACTIONS ON CIRCUITS AND SYSTEMS I-REGULAR PAPERS | IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC | Published : 2009

Abstract

In this paper, a new latent variable model is proposed for the realization of 2-D single-input-single-output linear causal systems. For the general (n, m)th-order 2-D system, the latent variable model obtained here is implicit when n ≠ m. Importantly, however, even in this case, the model is recursively computable. The advantage of the proposed realization is that the dimension of the latent variable is nm, which is much smaller than that for existing latent variable realizations, such as Fornasini-Marchesini (FM) and Roesser models. Given a particular 2-D system, an algorithm is developed for further reducing the size of the realization. © 2009 IEEE.

Grants

Awarded by Australian Research Council


Awarded by National Natural Science Foundation of China


Awarded by Natural Science Foundation of Guangdong


Funding Acknowledgements

This work was supported in part by the Australian Research Council under Grant DP0664789 and Grant DP0986577, by the National Natural Science Foundation of China under Grant 60504022, and by the Natural Science Foundation of Guangdong Province under Grant 05003343. This paper was recommended by Associate Editor A. Kummert.