To enable more accurate estimation of connectivity, we propose a data-driven and theoretically grounded framework for optimally designing perturbation inputs, based on formulating the neural model as ...
We have considerable expertise in MPC as a powerful tool for providing optimal control in dynamic environments, ensuring real-time performance and adaptability. Our work includes developing predictive ...
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