IEEE

AI Deep Learning Optimization for Compact Dual-Polarized High-Isolation Antenna Using Backpropagation Algorithm

Abstract: An artificial intelligence deep learning algorithm is proposed to analyze a dual-polarized high-isolation antenna effectively. The method is a building model of multi-input target ...
The Manila Times

WiMi Explores the Application of Neural Networks in Parameter Optimization for Dual-Field Quantum Key Distribution

WiMi Hologram Cloud Inc. (NASDAQ: WiMi) ('WiMi' or the 'Company'), a leading global Hologram Augmented Reality ('AR') Technology provider, announced that they are researching the use of neural ...
GitHub

Xiaohan-Chen/transfer-learning-fault-diagnosis-pytorch

For further introductions to transfer learning in bearing fault diagnosis, please read our paper. And if you find this repository useful and use it in your works, please cite our paper, thank you~: ...

In 1986, three scientists improved backpropagation, making neural networks learn effectively from data

A groundbreaking 1986 technique called backpropagation revolutionized artificial intelligence, enabling computers to learn ...
IEEE

Toward on-chip acceleration of the backpropagation algorithm using nonvolatile memory

Abstract: By performing computation at the location of data, non-Von Neumann (VN) computing should provide power and speed benefits over conventional (e.g., VN-based) approaches to data-centric ...
GitHub

DDPG: Deep Deterministic Policy Gradients

The algorithm consists of two networks, an Actor and a Critic network, which approximate the policy and value functions of a reinforcement learning problem. The name DDPG, or Deep Deterministic Policy ...