Abstract
In this chapter, the method of Lyapunov functions for differential equations with piecewise constant argument considered in Chapter 5 is applied to a model of recurrent neural networks (RNNs). The model includes both advanced and delayed arguments. We obtain sufficient conditions for global exponential stability of the equilibrium point. The feasibility of the results are illustrated by examples with numerical simulations.
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© 2011 Atlantis Press
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Akhmet, M. (2011). Stability of Neural Networks. In: Nonlinear Hybrid Continuous/Discrete-Time Models. Atlantis Studies in Mathematics for Engineering and Science, vol 8. Atlantis Press. https://doi.org/10.2991/978-94-91216-03-9_8
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DOI: https://doi.org/10.2991/978-94-91216-03-9_8
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Publisher Name: Atlantis Press
Print ISBN: 978-94-91216-02-2
Online ISBN: 978-94-91216-03-9
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