Improved results on stability and \(H_\infty\) performance analysis for discrete-time neural networks with time-varying delay
From MaRDI portal
Publication:2158556
DOI10.1007/s40314-022-01902-6OpenAlexW4281654993MaRDI QIDQ2158556
Qiao Chen, Hua Liu, Xin-Ge Liu, Peiyu Guo, Xiayun Li
Publication date: 26 July 2022
Published in: Computational and Applied Mathematics (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1007/s40314-022-01902-6
Related Items (1)
Cites Work
- Unnamed Item
- Unnamed Item
- Improved criteria on robust stability and \(\mathcal{H}_\infty\) performance for linear systems with interval time-varying delays via new triple integral functionals
- Improvement on the feasible region of \(\mathcal H_\infty\) performance and stability for systems with interval time-varying delays via augmented Lyapunov-krasivskii functional
- Auxiliary function-based summation inequalities and their applications to discrete-time systems
- Reciprocally convex approach to stability of systems with time-varying delays
- Further improvement of Jensen inequality and application to stability of time-delayed systems
- A delay-partitioning approach to the stability analysis of discrete-time systems
- Discrete inequalities based on multiple auxiliary functions and their applications to stability analysis of time-delay systems
- Exponential stability result for discrete-time stochastic fuzzy uncertain neural networks
- Improved criteria on delay-dependent stability for discrete-time neural networks with interval time-varying delays
- Reliable filter design for discrete-time neural networks with Markovian jumping parameters and time-varying delay
- A novel approach to \(H_\infty\) performance analysis of discrete-time networked systems subject to network-induced delays and malicious packet dropouts
- New \(H_\infty\) state estimation criteria of delayed static neural networks via the Lyapunov-Krasovskii functional with negative definite terms
- Extended dissipativity analysis for discrete-time delayed neural networks based on an extended reciprocally convex matrix inequality
- A new delay-variation-dependent stability criterion for delayed discrete-time systems
- \(H_\infty\) performance analysis for delayed Markovian jump neural networks via the Lyapunov-Krasovskii functional with delay-product-type terms
- Stability and passivity analysis of discrete-time linear systems with time-varying delay
- A new result on \(H_\infty\) performance state estimation for static neural networks with time-varying delays
- Delay-Variation-Dependent Stability of Delayed Discrete-Time Systems
- Stability of Discrete-Time Systems With Time-Varying Delays via a Novel Summation Inequality
- Free-Matrix-Based Integral Inequality for Stability Analysis of Systems With Time-Varying Delay
- Delay-Dependent Reciprocally Convex Combination Lemma for the Stability Analysis of Systems with a Fast-Varying Delay
- Summation Inequalities to Bounded Real Lemmas of Discrete-Time Systems With Time-Varying Delay
- Stability of time-delay systems
This page was built for publication: Improved results on stability and \(H_\infty\) performance analysis for discrete-time neural networks with time-varying delay
