Understanding the neural mechanisms underlying associative threat learning is essential for advancing behavioral models of threat and adaptation. We investigated distinct activation patterns across ...
Abstract: This paper proposes a finite-time sliding mode adaptive tracking control strategy with a neural network disturbance observer to address problems of inertia uncertainties, unknown external ...
Institute of Digitized Medicine and Intelligent Technology, Wenzhou Medical University, Wenzhou 325000, P. R. China ...
Abstract: Dynamic stream learning, which emphasizes high-velocity, single-pass, real-time responses to arriving data, is revealing new challenges to the standard machine learning paradigm. In ...
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