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A new prediction error identification method is proposed to identify multi-input-multi-output (MIMO) processes and the initial state. It linearizes the model output with respect to the model parameters so that optimal model parameters can be obtained in an analytic way. And, it has potential to provide a faster convergence rate and a better local minimum in solving the nonlinear optimization problem.
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