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Delay-Dependent and Delay-Independent Stability Conditions of Delayed Cellular Neural Networks

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Neural Information Processing (ICONIP 2006)

Part of the book series: Lecture Notes in Computer Science ((LNTCS,volume 4232))

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Abstract

By using the saturation linearity of the output functions of neurons in cellular neural networks, and by adopting the method of decomposing the state space to sub-regions, the mathematical equations of delayed cellular neural networks are rewritten to be the form of linear differential difference equations in the neighbourhood of each equilibrium, which is an interior point of some sub-region. Based on this linear form and by using the stability theory of linear differential difference equations and the tool of M-matrix, delay-dependent and delay-independent stability algebraic criteria are obtained. All results obtained in this paper need only to compute the eigenvalues of some matrices or to examine the matrices to be M-matrix or to verify some inequalities to be holden.

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© 2006 Springer-Verlag Berlin Heidelberg

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Liao, W., Wang, D., Xu, Y., Liao, X. (2006). Delay-Dependent and Delay-Independent Stability Conditions of Delayed Cellular Neural Networks. In: King, I., Wang, J., Chan, LW., Wang, D. (eds) Neural Information Processing. ICONIP 2006. Lecture Notes in Computer Science, vol 4232. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11893028_59

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  • DOI: https://doi.org/10.1007/11893028_59

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-540-46479-2

  • Online ISBN: 978-3-540-46480-8

  • eBook Packages: Computer ScienceComputer Science (R0)

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