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Exponential stability of Hopfield neural networks of neutral type with multiple time-varying delays
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What this work says
Outgoing claims: the papers this work cites, builds on, or argues with.
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Introduction to Functional Differential Equations
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Novel results on stability analysis of neutral-type neural networks with additive time-varying delay components and leakage delay
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Pattern recognition by homomorphic graph matching using Hopfield neural networks
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Delay differential equations with applications in population dynamics
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Non-fragile delay feedback control for neutral stochastic Markovian jump systems with time-varying delays
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Improved delay-dependent stability of neutral type neural networks with distributed delays
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An analysis of stability of neutral-type neural systems with constant time delays
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New stability analysis for neutral type neural networks with discrete and distributed delays using a multiple integral approach
inferredcites →https://doi.org/10.1016/j.jfranklin.2018.11.002openalex-snapshot
A modified Lyapunov functional with application to stability of neutral-type neural networks with time delays
inferredcites →https://doi.org/10.1016/j.matcom.2021.02.001openalex-snapshot
New results on dynamics of neutral type HCNNs with proportional delays
inferredcites →https://doi.org/10.1016/j.matpr.2017.09.222openalex-snapshot
Singular value Decomposition applied to Associative Memory of Hopfield Neural Network
inferredcites →https://doi.org/10.1016/j.nahs.2019.03.009openalex-snapshot
Admissibility analysis and stabilization for neutral descriptor hybrid systems with time-varying delays
inferredcites →https://doi.org/10.1016/j.neucom.2008.10.018openalex-snapshot
Delay-dependent stability of neutral type neural networks with distributed delays
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New delay-dependent stability criteria for switched Hopfield neural networks of neutral type with additive time-varying delay components
inferredcites →https://doi.org/10.1016/j.neucom.2015.05.035openalex-snapshot
New delay-dependent stability criteria for neutral-type neural networks with mixed random time-varying delays
inferredcites →https://doi.org/10.1016/j.neucom.2016.02.034openalex-snapshot
Stability analysis of Hopfield neural networks perturbed by Poisson noises
inferredcites →https://doi.org/10.1016/j.neucom.2017.01.037openalex-snapshot
Finite-time stability analysis for neutral-type neural networks with hybrid time-varying delays without using Lyapunov method
inferredcites →https://doi.org/10.1016/j.neucom.2017.07.001openalex-snapshot
Global asymptotic and robust stability of inertial neural networks with proportional delays
inferredcites →https://doi.org/10.1016/j.neucom.2017.08.060openalex-snapshot
Existence–uniqueness and stability of reaction–diffusion stochastic Hopfield neural networks with S-type distributed time delays
inferredcites →https://doi.org/10.1016/j.neucom.2017.10.021openalex-snapshot
Multiple integral Lyapunov approach to mixed-delay-dependent stability of neutral neural networks
inferredcites →https://doi.org/10.1016/j.neucom.2018.08.089openalex-snapshot
Further results on stability and synchronization of fractional-order Hopfield neural networks
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Stability analysis of high order neural networks with proportional delays
inferredcites →https://doi.org/10.1016/j.neunet.2016.03.007openalex-snapshot
Global exponential stability of complex-valued neural networks with both time-varying delays and impulsive effects
inferredcites →https://doi.org/10.1016/j.neunet.2019.01.017openalex-snapshot
Stability analysis of Cohen–Grossberg neural networks of neutral-type: Multiple delays case
inferredcites →https://doi.org/10.1016/j.neunet.2020.02.020openalex-snapshot
New criteria for global stability of neutral-type Cohen–Grossberg neural networks with multiple delays
inferredcites →https://doi.org/10.1016/j.neunet.2020.05.014openalex-snapshot
Generalized norm for existence, uniqueness and stability of Hopfield neural networks with discrete and distributed delays
inferredcites →https://doi.org/10.1016/j.neunet.2020.06.013openalex-snapshot
A new Lyapunov functional for stability analysis of neutral-type Hopfield neural networks with multiple delays
inferredcites →https://doi.org/10.1016/j.physleta.2010.02.043openalex-snapshot
A novel delay-dependent criterion for delayed neural networks of neutral type
inferredcites →https://doi.org/10.1016/s0076-5392(08)x6118-1openalex-snapshot
Stability of Functional Differential Equations
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Neural networks and physical systems with emergent collective computational abilities.
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Neurons with graded response have collective computational properties like those of two-state neurons.
inferredcites →https://doi.org/10.1093/imamat/hxt027openalex-snapshot
Global exponential stabilization of impulsive neural networks with unbounded continuously distributed delays
inferredcites →https://doi.org/10.1109/31.1783openalex-snapshot
Neural networks for nonlinear programming
inferredcites →https://doi.org/10.1109/tcsii.2006.876385openalex-snapshot
Delay-dependent exponential stability of delayed neural networks with time-varying delay
inferredcites →https://doi.org/10.1109/tnnls.2014.2347290openalex-snapshot
Stability Analysis of Distributed Delay Neural Networks Based on Relaxed Lyapunov–Krasovskii Functionals
inferredcites →https://doi.org/10.15388/na.2018.6.6openalex-snapshot
Fixed-time control of delayed neural networks with impulsive perturbations
inferredcites →https://doi.org/10.3934/mbe.2018069openalex-snapshot
Review of stability and stabilization for impulsive delayed systems
inferredcites →https://doi.org/10.3934/qfe.2019.4.608openalex-snapshot
BOMD: Building Optimization Models from Data (Neural Networks based Approach)
What points at this work
Incoming claims: where this work appears in other papers’ reference lists and arguments.
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Observer Design for Generalized Quasi‐One‐Sided Lipschitz Nonlinear Neutral Systems With Multiple Delays
inferred← citeshttps://doi.org/10.1007/978-981-96-1177-5_6openalex-snapshot
Global Exponential Stability and Stabilization
inferred← citeshttps://doi.org/10.1007/s11063-023-11375-1openalex-snapshot
Global Results on Exponential Stability of Neutral Cohen–Grossberg Neural Networks Involving Multiple Neutral and Discrete Time-Varying Delays: A Method Based on System Solutions
inferred← citeshttps://doi.org/10.1016/j.jfranklin.2022.11.012openalex-snapshot
Exponential stability criteria for linear neutral systems with applications to neural networks of neutral type
inferred← citeshttps://doi.org/10.1016/j.neucom.2022.03.068openalex-snapshot
Global exponential stability of neutral-type Cohen–Grossberg neural networks with multiple time-varying neutral and discrete delays
inferred← citeshttps://doi.org/10.1134/s1055134425040042openalex-snapshot
Systems of Neutral Type Equations and a Model of Hopfield Neural Network
inferred← citeshttps://doi.org/10.1371/journal.pone.0317398openalex-snapshot
Research on reachable set boundary of neutral system with various types of disturbances
inferred← citeshttps://doi.org/10.2298/fil2318021qopenalex-snapshot
Stability analysis of periodic solutions of the neutral-type neural networks with impulses and time-varying delays
inferred← citeshttps://doi.org/10.3390/e25040620openalex-snapshot
Unpredictable and Poisson Stable Oscillations of Inertial Neural Networks with Generalized Piecewise Constant Argument
inferred← citeshttps://doi.org/10.3390/math10121963openalex-snapshot
A Novel Multi-Objective Hybrid Election Algorithm for Higher-Order Random Satisfiability in Discrete Hopfield Neural Network
inferred← citeshttps://doi.org/10.3390/math14173075openalex-snapshot
A General Framework for Stability Analysis of Neutral Cohen–Grossberg Neural Networks with Discrete Delay Terms
inferred← citeshttps://doi.org/10.3934/math.20231372openalex-snapshot
Stability of delay Hopfield neural networks with generalized proportional Riemann-Liouville fractional derivative
inferred← citeshttps://doi.org/10.3934/math.2023978openalex-snapshot
Exponential stability of Cohen-Grossberg neural networks with multiple time-varying delays and distributed delays
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Stability analysis for bidirectional associative memory neural networks: A new global asymptotic approach
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