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 ...
Abstract: In this article, a new approximate joint diagonalization problem is formulated for the blind separation of possibly dependent sources, modelled as widely linear autoregressive moving average ...
Abstract: In this paper, we consider optimal control problems (OCPs) applied to large-scale linear dynamical systems with a large number of states and inputs. We attempt to reduce such problems into a ...
ParAMD is a shared memory parallel implementation of the approximate minimum degree (AMD) algorithm with multiple elimination via distance-2 independent sets. For more information, please read our ...
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