AIMC Topic: Hopfield Neural Networks

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State-space kinetic Ising model reveals task-dependent entropy flow in sparsely active nonequilibrium neuronal dynamics.

Nature communications
Neuronal ensemble activity, including coordinated and oscillatory patterns, exhibits hallmarks of nonequilibrium systems with time-asymmetric trajectories to maintain their organization. However, assessing time asymmetry from neuronal spiking activit...

Plane coexistence behaviors for Hopfield neural network with two-memristor-interconnected neurons.

Neural networks : the official journal of the International Neural Network Society
Memristors are commonly used as the connecting parts of neurons in brain-like neural networks. The memristors, unlike the existing literature, possess the capability to function as both self-connected synaptic weights and interconnected synaptic weig...

Training forecast to football athletes using Hopfield neural networks based on Markov matrix.

PloS one
This paper proposes a neural network based on the Markov probability transition matrix to predict the training performance of football athletes. Firstly, seven training indicators affecting the training performance are designed by the Event-group tra...