Dynamics analysis on a class of delayed neural networks involving inertial terms
Jian Zhang, Chuangxia Huang
Abstract
Abstract This paper explores a class of unbounded distributed delayed inertial neural networks. By introducing some new differential inequality analysis and abandoning the traditional order reduction technique, some new assertions are derived to verify the global exponential stability of the addressed networks, which improve and generalize some recently published articles. Finally, two cases of numerical examples and simulations are given to illustrate these analytical conclusions.
Topics & Concepts
Ordinary differential equationInertial frame of referenceClass (philosophy)Dynamics (music)Artificial neural networkMathematicsApplied mathematicsPartial differential equationStability (learning theory)Exponential stabilityComputer scienceReduction (mathematics)Control theory (sociology)Differential equationMathematical analysisArtificial intelligenceNonlinear systemClassical mechanicsGeometryMachine learningControl (management)PhysicsQuantum mechanicsAcousticsNeural Networks Stability and SynchronizationNeural Networks and Applicationsstochastic dynamics and bifurcation