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Synchronization of Uncertain Neural Networks with Additive Time-Varying Delays and General Activation Function

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Abstract

This paper discusses the drive-response synchronization of uncertain neural networks with additive time-varying delays. A general activation function is considered to include more information on the cross-terms of the activation function, through which less conservative delay-dependent stability conditions are acquired using generalized free weighting matrix inequality (GFWMI). The usage of GFWMI leads to a stability criterion with non-linear matrix inequality involving two time-varying delays. A newly developed quadratic inequality is used to transform the non-linear matrix inequality into a linear matrix inequality. Finally, the feasibility and superiority of the derived results are examined through numerical examples. The maximum allowable upper bounds are calculated in each example from which the advantages of the proposed results are expounded by comparing recent related literature.

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Authors and Affiliations

  1. Department of Mathematics, The Gandhigram Rural Institute (Deemed to be University), Gandhigram, Tamil Nadu, India

    A. Karnan & G. Nagamani

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  1. A. Karnan
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  2. G. Nagamani
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Karnan, A., Nagamani, G. Synchronization of Uncertain Neural Networks with Additive Time-Varying Delays and General Activation Function. Neural Process Lett 55, 4951–4971 (2023). https://doi.org/10.1007/s11063-022-11074-3

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