Dynamical analysis of a novel 4-neurons based Hopfield neural network: emergences of antimonotonicity and coexistence of multiple stable states
| Autor: | B. P. Leutcha, Hilaire Bertrand Fotsin, Jacques Kengne, Zeric Tabekoueng Njitacke, T. Fonzin Fozin |
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| Rok vydání: | 2019 |
| Předmět: |
Physics
0209 industrial biotechnology Control and Optimization Quantitative Biology::Neurons and Cognition Artificial neural network Mechanical Engineering Chaotic 02 engineering and technology 01 natural sciences Matrix (mathematics) 020901 industrial engineering & automation Fractal Control and Systems Engineering Modeling and Simulation 0103 physical sciences Statistical physics Electrical and Electronic Engineering 010301 acoustics Civil and Structural Engineering Stable state |
| Zdroj: | International Journal of Dynamics and Control. 7:823-841 |
| ISSN: | 2195-2698 2195-268X |
| Popis: | In this contribution, we investigate the dynamics of a novel model of 4-neurons based Hopfield neural networks. Our analyses highlight complex phenomena such as chaotic and periodic behaviors which have been classified by Panahi et al. (Chaos Solitons Fractals 105:150–156, 2017) as some brain behaviors. More interestingly, it has been revealed several sets of synaptic weights matrix for which the proposed HNNs displays multiple coexisting stable states including two, four and six disjoined orbits. Basins of attraction of coexisting stable states have been computed showing different regions in which each solution can be captured. Beside the presence of coexisting bifurcations, the model displays remerging Feigenbaum trees bifurcations also known as antimonotonicity for some judicious sets of synaptic weights. PSpice investigations are finally used to confirm results of the theoretical investigations. |
| Databáze: | OpenAIRE |
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