Abstract: This article focuses on the low-conservative stability criteria of delayed neural networks (DNNs). To achieve this goal, new techniques are developed to effectively utilize more ...
Abstract: This study explores the development of nonlinear activation functions in reinforcement learning through evolutionary computation. Traditional activation functions like Rectified Linear-Unit ...
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