Global stability for functional differential equations with infinite delay and applications to Hopfield-type neural networks

Key Points

• Global stability is achieved for functional differential equations with infinite delay, impacting dynamic systems.
• Key evidence includes mathematical proofs demonstrating stability across varying conditions and parameters.
• Analysis focuses on hopfield-type neural networks, exploring their theoretical frameworks for stability.
• These findings highlight the need for further validations in practical applications of neural networks.