Exponential Stability of Positive Recurrent Neural Networks with Multi-proportional Delays

This paper presents some new results on the existence, uniqueness and generalized exponential stability of a positive equilibrium for positive recurrent neural networks with multi-proportional delays. Based on the differential inequality techniques, a testable condition is established to guarantee that all solutions of the considered system converge exponentially to a unique positive equilibrium. The effectiveness of the obtained results is illustrated by a numerical example.

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