Fixed/Preassigned-Time Synchronization of Complex Variable BAM Neural Networks with Time-Varying Delays

This paper is mainly devoted to fixed/preassigned-time synchronization problem for a type of full complex-variable BAM neural networks (BAMNNs) by means of direct analysis method to replace the classical decomposition approach. Above all, under the framework of the complex-valued signum function and two different forms of norms, several effective complex-valued control strategies are directly developed to ensure fixed-time synchronization, and the derived criteria are less conservative than the previous related results. In addition, the preassigned-time synchronization is also considered by directly designing some complex-valued control laws with bounded control gains, in which the synchronization time can be preset arbitrarily in advance within the actual allowable range. The theoretical results are lastly supported via numerical examples.

Automated summary

This paper addresses the fixed/preassigned-time synchronization problem for a type of full complex-variable BAM neural networks (BAMNNs), using direct analysis method instead of the classical decomposition approach. The paper proposes effective complex-valued control strategies based on the complex-valued signum function and two different forms of norms, which ensure fixed-time synchronization with less conservatism compared to previous results. The paper also considers preassigned-time synchronization by designing complex-valued control laws with bounded control gains, allowing the synchronization time to be arbitrarily preset within the allowable range. Numerical examples are provided to support the theoretical results.