Journal
MATHEMATICS
Volume 9, Issue 24, Pages -Publisher
MDPI
DOI: 10.3390/math9243321
Keywords
neural networks; finite-time passivity; linear matrix inequality; distributed delay; neutral system
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This research investigates finite-time passivity analysis of neutral-type neural networks with mixed time-varying delays. New sufficient conditions for finite-time stability and passivity are proposed and demonstrated through numerical examples. The proposed criteria are less conservative than prior studies in terms of larger time-delay bounds.
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.
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