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Global Exponential Stability of Fuzzy Cellular Neural Networks with Variable Delays

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Book cover Advances in Neural Networks - ISNN 2006 (ISNN 2006)

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Abstract

In this paper, the global exponential stability of fuzzy cellular neural networks with time-varying delays is studied. Without assuming the boundedness and differentiability of the activation functions, based on the properties of M-matrix, by constructing vector Liapunov functions and applying differential inequalities, the sufficient conditions ensuring existence, uniqueness, and global exponential stability of the equilibrium point of fuzzy cellular neural networks with variable delays are obtained.

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© 2006 Springer-Verlag Berlin Heidelberg

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Zhang, J., Ren, D., Zhang, W. (2006). Global Exponential Stability of Fuzzy Cellular Neural Networks with Variable 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_36

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  • DOI: https://doi.org/10.1007/11759966_36

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-34439-1

  • Online ISBN: 978-3-540-34440-7

  • eBook Packages: Computer ScienceComputer Science (R0)

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