Event-Triggered Synchronization of Multiple Fractional-Order Recurrent Neural Networks With Time-Varying Delays.
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- Record sourced from PubMed, PMID 34618678.
- Also identified by DOI 10.1109/TNNLS.2021.3116382.
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Abstract
This paper addresses the synchronization of multiple fractional-order recurrent neural networks (RNNs) with time-varying delays under event-triggered communications. Based on the assumption of the existence of strong connectivity or a spanning tree in the communication digraph, two sets of sufficient conditions are derived for achieving event-triggered synchronization. Moreover, an additional condition is derived to preclude Zeno behaviors. As a generalization of existing results, the criteria herein are also applicable to the event-triggered synchronization of multiple integer-order RNNs with or without delays. Two numerical examples are elaborated to illustrate the new results.