I have come across various ways of defining Artificial Neural Networks (ANNs). Many of them miss a fundamental characteristic ...

Engineers are in the early stages of harnessing Wi-Fi as a way to monitor heart rates, but don't expect to use your home ...

End to end, every segment of what we do is driven by some form of intelligence,” said Indira Uppuluri, SVP of supply chain ...

In this important study, the authors model reinforcement-learning experiments using a recurrent neural network. The work examines if the detailed credit assignment necessary for back-propagation ...

Over the past decade, deep learning (DL) techniques such as convolutional neural networks (CNNs) and long short-term memory (LSTM) networks have played a pivotal role in advancing the field of ...

Abstract: Unlike traditional feedforward neural networks, recurrent neural networks (RNNs) possess a recurrent connection that allows them to retain past information. This internal memory enables RNNs ...

This repository demonstrates a complete workflow for training and deploying neural networks directly inside MetaTrader 5. The goal is to show that the MQL5 language can handle custom machine learning ...

Abstract: To address the motion generation problem in distributed multimanipulator system operating in obstacles environment, a distributed slack barrier recurrent neural network (DSB-RNN) is proposed ...

ABSTRACT: Introduction: Nursing is an important link in the healthcare chain. Excessive workload is often associated with a decline in the quality of care provided and a compromise in patient safety.

The findings of this study are valuable, offering insights into the neural representation of reversal probability in decision-making tasks, with potential implications for understanding flexible ...