Finite-Time Passivity Analysis of Neutral-Type Neural Networks with Mixed Time-Varying Delays

Issaraporn Khonchaiyaphum, Nayika Samorn, Thongchai Botmart and Kanit Mukdasai
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Issaraporn Khonchaiyaphum: Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand
Nayika Samorn: Faculty of Agriculture and Technology, Nakhon Phanom University, Nakhon Phanom 48000, Thailand
Thongchai Botmart: Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand
Kanit Mukdasai: Department of Mathematics, Faculty of Science, Khon Kaen University, Khon Kaen 40002, Thailand

Mathematics, 2021, vol. 9, issue 24, 1-26

Abstract: This research study investigates the issue of finite-time passivity analysis of neutral-type neural networks with mixed time-varying delays. The time-varying delays are distributed, discrete and neutral in that the upper bounds for the delays are available. We are investigating the creation of sufficient conditions for finite boundness, finite-time stability and finite-time passivity, which has never been performed before. First, we create a new Lyapunov–Krasovskii functional, Peng–Park’s integral inequality, descriptor model transformation and zero equation use, and then we use Wirtinger’s integral inequality technique. New finite-time stability necessary conditions are constructed in terms of linear matrix inequalities in order to guarantee finite-time stability for the system. Finally, numerical examples are presented to demonstrate the result’s effectiveness. Moreover, our proposed criteria are less conservative than prior studies in terms of larger time-delay bounds.

Keywords: neural networks; finite-time passivity; linear matrix inequality; distributed delay; neutral system (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2021
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (2)

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