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A new stability criterion for bidirectional associative memory neural networks of neutral-type. (English) Zbl 1149.34345
Summary: The global asymptotic stability of an equilibrium is considered for continuous bidirectional associative memory (BAM) neural networks of neutral type by using the Lyapunov method. A new stability criterion is derived in terms of linear matrix inequality (LMI) to ascertain the global asymptotic stability of the BAM. The LMI can be solved easily by various convex optimization algorithms. A numerical example is illustrated to verify our result.

MSC:
34K20 Stability theory of functional-differential equations
92B20 Neural networks for/in biological studies, artificial life and related topics
Software:
LMI toolbox
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