This paper examines the quasi‐stabilization and synchronization of memristive neural networks in high dimensional forms. First, new criteria for the existence of the equilibrium point (EP) are delivered by contraction… Click to show full abstract
This paper examines the quasi‐stabilization and synchronization of memristive neural networks in high dimensional forms. First, new criteria for the existence of the equilibrium point (EP) are delivered by contraction mapping principle. Then, a new Lyapunov function described with one‐norm form is imported for quasi‐stabilization/synchronization of the system. Finally, two numerical examples containing simulations are given to demonstrate the effectiveness.
Keywords:
memristive neural;
neural networks;
stabilization synchronization;
quasi stabilization
Journal Title: Mathematical Methods in the Applied Sciences
Year Published: 2024
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Journal Title: Mathematical Methods in the Applied Sciences
Year Published: 2024
Link to full text (if available)
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recommendations!