Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  solve two problems in modeling polynomial vector-exponential trajectories dependent on two independent variables. In the first one  assume that the data-generating system has no inputs, and  compute a state representation of the most porful unfalsified model for this data. In the second instance  assume that the data-generating system is controllable and quarter-plane causal, and  compute a Roesser input-state-output model.  provide procedures for solving these identification problems, both based on the factorization of constant matrices directly constructed from the data, from which state trajectories can be computed.
['Paolo Rapisarda', 'Athanasios C. Antoulas']
I am writing a research paper on a idea State-Space Modeling of Two-Dimensional Vector-Exponential Trajectories
[{"from": "human", "value": "I am writing a research paper on a idea State-Space Modeling of Two-Dimensional Vector-Exponential Trajectories"}, {"from": "gpt", "value": "Thats a unique idea.You should consider the following idea to enhance your idea so that it would impact uniquely:  solve two problems in modeling polynomial vector-exponential trajectories dependent on two independent variables. In the first one  assume that the data-generating system has no inputs, and  compute a state representation of the most porful unfalsified model for this data. In the second instance  assume that the data-generating system is controllable and quarter-plane causal, and  compute a Roesser input-state-output model.  provide procedures for solving these identification problems, both based on the factorization of constant matrices directly constructed from the data, from which state trajectories can be computed."}]