<p>In this paper, which can be considered as an extension of our previous publication (Liu and Yu in Fract Calc Appl Anal 25:2040-2061, 2022) in same journal, we analyze the stability and synchronization for the discrete fractional-order neural network systems with mixed time delays. By new techniques, we give the proof of the discrete fractional-order Halanay inequality with mixed time delays, which contains both discrete and distributed time delays. Then, using this fractional-order Halanay inequality and constructing an appropriate Lyapunov function, we give the sufficient criteria of Mittag-Leffler stability and synchronization for the discrete fractional-order neural network systems with mixed time delays. Finally, an example is provided to illustrated one of the results.</p>

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Discrete fractional-order Halanay inequality with mixed time delays and applications in discrete fractional-order neural network systems

  • Xiang Liu,
  • Yongguang Yu

摘要

In this paper, which can be considered as an extension of our previous publication (Liu and Yu in Fract Calc Appl Anal 25:2040-2061, 2022) in same journal, we analyze the stability and synchronization for the discrete fractional-order neural network systems with mixed time delays. By new techniques, we give the proof of the discrete fractional-order Halanay inequality with mixed time delays, which contains both discrete and distributed time delays. Then, using this fractional-order Halanay inequality and constructing an appropriate Lyapunov function, we give the sufficient criteria of Mittag-Leffler stability and synchronization for the discrete fractional-order neural network systems with mixed time delays. Finally, an example is provided to illustrated one of the results.