Positive almost periodicity on SICNNs incorporating mixed delays and D operator
Chuangxia Huang, Bingwen Liu, Hedi Yang, Jinde Cao
Abstract
This article involves a kind of shunting inhibitory cellular neural networks incorporating D operator and mixed delays. First of all, we demonstrate that, under appropriate external input conditions, some positive solutions of the addressed system exist globally. Secondly, with the help of the differential inequality techniques and exploiting Lyapunov functional approach, some criteria are established to evidence the globally exponential stability on the positive almost periodic solutions. Eventually, a numerical case is provided to test and verify the correctness and reliability of the proposed findings.
Topics & Concepts
CorrectnessOperator (biology)Exponential stabilityReliability (semiconductor)MathematicsLyapunov functionControl theory (sociology)Stability (learning theory)Applied mathematicsArtificial neural networkComputer scienceAlgorithmControl (management)Artificial intelligenceNonlinear systemPower (physics)Machine learningQuantum mechanicsRepressorChemistryBiochemistryTranscription factorGenePhysicsNeural Networks Stability and SynchronizationAdvanced Mathematical Modeling in EngineeringCooperative Communication and Network Coding