Dissipativity and synchronization of fractional-order output-coupled neural networks with multiple adaptive coupling weights

Xiulan Zhang, YiYu Liu, Hongling Qiu and Heng Liu

Mathematics and Computers in Simulation (MATCOM), 2024, vol. 215, issue C, 306-322

Abstract: Different from the majority of existing results that focus on the passivity analysis of nonlinear systems, this paper attempts to analyze the more general QSR-dissipativity of fractional-order neural networks that own output coupling and multiple coupled weights, where outer coupling weights can be adjusted online by developing an adaptation law. Using the linear matrix inequality technique, several sufficient criteria that not only guarantee the QSR-dissipativity of the network system but also achieve global synchronization even under zero input are established. Of particular significance is the proposal of a fractional Lyapunov-like lemma, which plays a crucial role in verifying the asymptotic stability of synchronization errors. Finally, a simulation example is presented to verify the plausibility of the theoretical results.

Keywords: Fractional-order neural network; Output coupling; QSR-dissipativity; Synchronization; Adaptive weight (search for similar items in EconPapers)
Date: 2024
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Persistent link: https://EconPapers.repec.org/RePEc:eee:matcom:v:215:y:2024:i:c:p:306-322

DOI: 10.1016/j.matcom.2023.08.016

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