Abstract
In this paper, the global exponential stability of a class of recurrent cellular neural networks with reaction-diffusion and variable time delays was studied. When neural networks contain unbounded activation functions, it may happen that equilibrium point does not exist at all. In this paper, without assuming the boundedness, monotonicity and differentiability of the active functions, the algebraic criteria ensuring existence, uniqueness and global exponential stability of the equilibrium point of neural networks are obtained.
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© 2006 Springer-Verlag Berlin Heidelberg
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Zheng, W., Zhang, J., Zhang, W. (2006). Stability Analysis of Reaction-Diffusion Recurrent Cellular Neural Networks with Variable Time Delays. In: Wang, J., Yi, Z., Zurada, J.M., Lu, BL., Yin, H. (eds) Advances in Neural Networks - ISNN 2006. ISNN 2006. Lecture Notes in Computer Science, vol 3971. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11759966_33
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DOI: https://doi.org/10.1007/11759966_33
Publisher Name: Springer, Berlin, Heidelberg
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