In this study, a circuit technique and training algorithm that minimizes the effect of stuck-at-faults (SAFs) within a memristor crossbar array of neural networks (NNs) are presented. To improve the ...

This paper presents a dynamic model of wireless sensor networks (WSNs) and its application to sensor node fault detection. Recurrent neural networks (NNs) are used to model a sensor node, the node's ...

Artificial neural networks trained via reinforcement learning developed body-part-centered receptive fields that closely match those of biological peripersonal neurons.

This repository is the open source code for my latest work: "Through-the-Wall Radar Human Activity Recognition WITHOUT Using Neural Networks", submitted to arXiv. Fig. 1. Current works in this field ...

Thanks to the neural network, the researchers now suspect, for example, that the black hole at the center of the Milky Way is spinning almost at top speed. Its rotation axis points to Earth.