<p>This paper investigates the predefined-time synchronization of competitive neural networks with time-varying delays. The study focuses on the synchronization problem under predefined-time constraints, employing two novel controllers: one based on a hyperbolic cosine-sine function and the other on an error function. Based on the new predefined-time stability theorems, the predefined-time synchronization of competitive neural networks is investigated by designing some new feedback controllers, and sufficient conditions are derived to guarantee the predefined-time synchronization of addressed neural networks. Numerical examples are provided to illustrate the effectiveness of the proposed synchronization strategies.</p>

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Novel Predefined-time Stability Theorems With Applications to the Synchronization of Competitive Neural Networks With Time-varying Delays

  • El Abed Assali,
  • Pushpendra Kumar,
  • Tae H. Lee

摘要

This paper investigates the predefined-time synchronization of competitive neural networks with time-varying delays. The study focuses on the synchronization problem under predefined-time constraints, employing two novel controllers: one based on a hyperbolic cosine-sine function and the other on an error function. Based on the new predefined-time stability theorems, the predefined-time synchronization of competitive neural networks is investigated by designing some new feedback controllers, and sufficient conditions are derived to guarantee the predefined-time synchronization of addressed neural networks. Numerical examples are provided to illustrate the effectiveness of the proposed synchronization strategies.