Analysis of exponential stability for neutral stochastic Cohen-Grossberg neural networks with mixed delays

DOI10.1155/2019/4813103zbMath1453.34095OpenAlexW2949062089WikidataQ115521841 ScholiaQ115521841MaRDI QIDQ2296505

Zuoliang Xiong, Cuiping Yang, Tianqing Yang

Publication date: 18 February 2020

Published in: Discrete Dynamics in Nature and Society (Search for Journal in Brave)

Full work available at URL: https://doi.org/10.1155/2019/4813103

Mathematics Subject Classification ID

Stochastic ordinary differential equations (aspects of stochastic analysis) (60H10) Neural networks for/in biological studies, artificial life and related topics (92B20) Stability theory of functional-differential equations (34K20) Stochastic stability in control theory (93E15) Stochastic functional-differential equations (34K50) Neutral functional-differential equations (34K40)

Related Items (1)

Mean‐square exponential input‐to‐state stability of stochastic delayed recurrent neural networks with local Lipschitz condition

Cites Work

• Exponential input-to-state stability of stochastic Cohen-Grossberg neural networks with mixed delays
• Adaptive synchronization of Cohen-Grossberg neural network with mixed time-varying delays and stochastic perturbation
• Hopf bifurcation for neutral-type neural network model with two delays
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• New results on global exponential dissipativity analysis of memristive inertial neural networks with distributed time-varying delays
• On the existence and stability of the periodic solution in the Cohen-Grossberg neural network with time delay and high-order terms
• GLOBAL STABILITY ANALYSIS FOR A CLASS OF COHEN-GROSSBERG NEURAL NETWORK MODELS
• Absolute stability of global pattern formation and parallel memory storage by competitive neural networks
• Stability of stochastic delay neural networks

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