Discrete Roesser state models from 2D frequency data

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Abstract

We identify a general, i.e. not necessarily denominator-separable Roesser model from 2D discrete vector-geometric trajectories generated by a controllable, quarter-plane causal system. Our procedure consists of two steps: the first one is the computation of state trajectories from the factorization of constant matrices directly constructed from input-output data. The second step is the computation of the state, output, and input matrices of a Roesser model as solutions of a system of linear equations involving the given input-output data and the computed state trajectories.

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Rapisarda, P. (2019). Discrete Roesser state models from 2D frequency data. Multidimensional Systems and Signal Processing, 30(2), 591–610. https://doi.org/10.1007/s11045-018-0572-6

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