Non-ideal memristor synapse-coupled bi-neuron Hopfield neural network: Numerical simulations and breadboard experiments

Chengjie Chen; Han Bao; Mo Chen; Quan Xu; Bocheng Bao

doi:10.1016/j.aeue.2019.152894

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Non-ideal memristor synapse-coupled bi-neuron Hopfield neural network: Numerical simulations and breadboard experiments

Chengjie Chen Han Bao Mo Chen Quan Xu Bocheng Bao

Year: 2019 Journal: AEU - International Journal of Electronics and Communications Vol: 111 Pages: 152894-152894 Publisher: Elsevier BV

DOI: 10.1016/j.aeue.2019.152894

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Keywords:

Memristor Breadboard Equilibrium point Artificial neural network Saddle point Attractor Synapse Ideal (ethics) Chaotic Bifurcation Coupling (piping) Topology (electrical circuits) Biological neuron model Physics Control theory (sociology) Computer science Mathematics Mathematical analysis Materials science Artificial intelligence Nonlinear system Engineering Geometry Quantum mechanics Electronic engineering Neuroscience

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Advanced Memory and Neural Computing

Physical Sciences → Engineering → Electrical and Electronic Engineering

stochastic dynamics and bifurcation

Physical Sciences → Physics and Astronomy → Statistical and Nonlinear Physics

Neural dynamics and brain function

Life Sciences → Neuroscience → Cognitive Neuroscience

Non-ideal memristor synapse-coupled bi-neuron Hopfield neural network: Numerical simulations and breadboard experiments

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