Exponential p-stability of impulsive stochastic Cohen-Grossberg neural networks with mixed delays
Mathematics and Computers in Simulation
Robust stability of uncertain fuzzy Cohen-Grossberg BAM neural networks with time-varying delays
Expert Systems with Applications: An International Journal
p-Moment stability of stochastic differential equations with impulsive jump and Markovian switching
Automatica (Journal of IFAC)
Existence and learning of oscillations in recurrent neural networks
IEEE Transactions on Neural Networks
Expert Systems with Applications: An International Journal
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In this paper, we investigate a class of delayed neural networks with impulsive and stochastic effects. By establishing an L- operator delay differential inequality with impulses and using the stochastic analysis technique, some sufficient conditions are derived to ensure the existence and global exponential stability of periodic solution for the addressed neural networks. Those conditions only including related parameters of neural networks can be easily checked by simple algebraic methods. Finally, two examples and their simulations are given to show the feasibility and effectiveness of our results.