Abstract
In the paper, the reaction-diffusion neural network models with both variable time delays and unbounded delay are investigated. These models contain weaker activation functions than partially or globally Lipschitz continuous functions. Without assuming the boundedness, monotonicity and differentiability of the active functions, algebraic criteria ensuring existence, uniqueness and global exponential stability of the equilibrium point are obtained.
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Zheng, W., Zhang, J., Zhang, W. (2006). Global Exponential Stability of Reaction-Diffusion Neural Networks with Both Variable Time Delays and Unbounded Delay. In: Huang, DS., Li, K., Irwin, G.W. (eds) Intelligent Computing. ICIC 2006. Lecture Notes in Computer Science, vol 4113. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11816157_43
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DOI: https://doi.org/10.1007/11816157_43
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-37271-4
Online ISBN: 978-3-540-37273-8
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