Coexistence behavior of asymmetric attractors in hyperbolic-type memristive Hopfield neural network and its application in image encryption
Xiaoxia 晓霞 Li 李,
Qianqian 倩倩 He 何,
Tianyi 天意 Yu 余
et al.
Abstract:The neuron model has been widely employed in neural-morphic computing systems and chaotic circuits. This study aims to develop a novel circuit simulation of a 3-neuron Hopfield neural network with coupled hyperbolic memristors through the modification of a single coupling connection weight. The bistable mode of the hyperbolic mHNN, characterized by the coexistence of asymmetric chaos and periodic attractors, is effectively demonstrated through the utilization of conventional nonlinear analysis techniques. Thes… Show more
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