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Input-to-state stability (ISS) analysis for dynamic neural networks. (English) Zbl 0956.68133
Summary: A novel approach to assess the stability of dynamic neural networks is presented. Using a Lyapunov function, we determine conditions to guarantee input-to-state stability which also ensures global asymptotic stability. The applicability of these conditions is illustrated by two examples.
MSC:
68T05Learning and adaptive systems
92B20General theory of neural networks (mathematical biology)