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Passivity Analysis of Non-autonomous Discrete-Time Inertial Neural Networks with Time-Varying Delays

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Abstract

This paper addresses the passivity problem for delayed non-autonomous discrete-time inertial neural networks (NDINN), including the discrete-time switched inertial neural networks (DSINN) with state-dependent discontinuous right-hand side as its special case. First, we take a linear transformation to transform the original network into first-order difference equations. Second, by utilizing the Lyapunov direct method and with the help of the property of maximum singular value, we present a passivity criterion for the NDINN with delay-dependent linear matrix inequalities. Combining with the characteristic function method, the proposed analytical approach for NDINN is further extended to the DSINN. Finally, two simulation examples validate the efficacy of the analytical results.

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Authors and Affiliations

  1. Department of Automation, Xiamen University, Xiamen, 361005, China

    Xuan Chen & Dongyun Lin

  2. School of Physics and Electronic Science, Guizhou Normal University, Guiyang, 550025, China

    Xuan Chen

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  1. Xuan Chen
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  2. Dongyun Lin
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Correspondence to Dongyun Lin.

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This work is supported by the National Natural Science Foundation of China (61873219) .

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Chen, X., Lin, D. Passivity Analysis of Non-autonomous Discrete-Time Inertial Neural Networks with Time-Varying Delays. Neural Process Lett 51, 2929–2944 (2020). https://doi.org/10.1007/s11063-020-10235-6

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  • DOI: https://doi.org/10.1007/s11063-020-10235-6

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