This valuable study uses EEG and computational modeling to investigate hemispheric oscillatory asymmetries in unilateral spatial neglect. The work benefits from rare patient data and a careful ...

Abstract: Hard-to-model, often nonlinear dynamics limit the tracking performance of physical-model-based feedforward control in medical interventional X-ray (IX) systems. In this article, these ...

Neural networks are algorithmic systems created based on the principle of the human nervous system. They consist of many ...

I have come across various ways of defining Artificial Neural Networks (ANNs). Many of them miss a fundamental characteristic of theirs. An ANN is a machine learning model. Like all machine learning ...

Networks are systems comprised of two or more connected devices, biological organisms or other components, which typically ...

Learn how to build a fully connected, feedforward deep neural network from scratch in Python! This tutorial covers the theory, forward propagation, backpropagation, and coding step by step for a hands ...

Abstract: This paper proposes a feedforward compensation strategy based on Parallel GRU-Transformer neural network to address the issues of large tracking errors and insufficient stability of multi ...

1 KNDS Deutschland GmbH & Co. KG, Munich, Germany 2 Institute for Software Technology, University of the Bundeswehr Munich, Neubiberg, Germany Artificial intelligence (AI) has emerged as a ...

Machine learning and neural nets can be pretty handy, and people continue to push the envelope of what they can do both in high end server farms as well as slower systems. At the extreme end of the ...