Stability analysis of inertial neural networks: A case of almost anti‐periodic environment
Adnène Arbi, Najeh Tahri
Abstract
In this paper, a class of inertial neural networks with time delays is considered. By developing an approach based on differential inequality techniques coupled with Lyapunov function method, some assertions are demonstrated to guarantee the exponential stability of almost anti‐periodic solutions for the dynamical system described the model. Finally, two numerical examples to illustrate the feasibility of our theoretical outcomes.
Topics & Concepts
Inertial frame of referenceMathematicsLyapunov functionArtificial neural networkExponential stabilityControl theory (sociology)Applied mathematicsClass (philosophy)Stability (learning theory)Dynamical systems theoryFunction (biology)Computer scienceArtificial intelligenceNonlinear systemControl (management)Classical mechanicsMachine learningEvolutionary biologyPhysicsBiologyQuantum mechanicsNeural Networks Stability and SynchronizationNeural Networks and ApplicationsStability and Controllability of Differential Equations