Absolute Stability of Hopfield Neural Network
This paper presents some new results for the absolute stability of Hopfield neural networks with activation functions chosen from sigmoidal functions which have unbounded derivatives. Detailed discussions are also given to the relation and difference of absolute stabilities between neural networks and Lurie systems with multiple nonlinear controls. Although the basic idea of the absolute stability of neural networks comes from that of Lurie control systems, it provides a very useful practical model for the study of Lurie control systems.
KeywordsNeural Network Equilibrium Point Lyapunov Exponent Absolute Stability Global Optimization Problem
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