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.
Highlights
The following finite-time boundedness analysis of neutral-type neural networks with mixed time-varying delays is discussed in this subsection
The new systems have been used to derive the analysis of finite-time passivity analysis of neutral-type neural networks with mixed time-varying delays
We are investigating the creation of sufficient conditions for finite boundness, finite-time stability and finite-time passivity, which has not been performed before
Summary
We begin by explaining various notations and lemmas that will be used throughout the study. For each positive definite symmetric matrix P7 , positive real constant μ M and vector function ξ : [−μ M , 0] → Rn such that the following integral is well defined, the following is obtained. For any constant symmetric positive definite matrix P6 ∈ Rn×n , μ(t) is a discrete time-varying delay with (2), vector function ξ : [−μ M , 0] → Rn such that the integrations concerned are well defined, the following is the case. 0, μ(t) is a discrete time-varying delay with (2) and vector function ξ : [−μ M , 0] → Rn such that the following integration is well defined: Rn×n ,. For a positive definite matrix P8 , P9 > 0 and any continuously differentiable function ξ : [ a, b] → Rn , the following inequality holds:.
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