IEEE

A Data-Driven Distributed Recurrent Neural Network for a Collaborative System of Multiple Redundant Manipulators With Unknown Structure

Abstract: This article proposes a novel data-driven distributed recurrent neural network (DDD-RNN) based on neurodynamics principles to address the challenge of precise collaborative motion generation ...
The Tech Edvocate

How to create neural network

Spread the love“`html Understanding how to create a neural network can be a game-changer in the fields of artificial intelligence and machine learning. As industries increasingly rely on data-driven ...
IEEE

Generating Simple Cyclic Memristive Neural Network Circuit With Controllable Multiscroll Attractors and Multivariable Amplitude Control

Abstract: Due to their synaptic-like characteristics and memory properties, memristors are often used in neuromorphic circuits, particularly neural network circuits. However, most of the existing ...
Nature

Turing universal neural networks do not require global clocks

Recurrent neural networks were proven to be Turing universal in the 1990s, motivating computational complexity studies of spiking networks, neural Turing machines with differentiable activations, and ...
Nature

Orbital angular momentum multiplexing diffractive neural networks for high-capacity optical inference

Deep diffractive neural networks have emerged as an all-optical computing paradigm that overcomes the bottlenecks of traditional electronic computing. However, traditional deep diffractive neural ...