Improved exponential stability of time delay neural networks via separated-matrix-based integral inequalities

Key Points

• Exponential stability of time delay neural networks is significantly improved with separated-matrix-based integral inequalities.
• Key metric changes reflect up to a 40% increase in stability under varying delay conditions and network structures.
• Observational analysis utilizing advanced integral inequalities examines the stability of neural networks with time delays.
• These findings highlight the potential for better performance in complex systems, while necessitating further validation in practical scenarios.