Identification of spatially distributed discrete-time state-space models*

In this paper we propose a computationally efficient algorithm for identifying spatially distributed discrete-time state-space models. In the case of identifying spatially invariant distributed systems, the computational complexity of the proposed algorithm scales linearly with the number of local subsystems. In the case of identifying spatially varying distributed systems the computational complexity of the proposed algorithm scales quadratically with the number of local subsystems. We demonstrate the effectiveness of the proposed identification algorithm by performing numerical tests.