Global asymptotic stability of neutral type fractional‐order memristor‐based neural networks with leakage term, discrete and distributed delays
M. Syed Ali, M. Hymavathi, Sumit Saroha, R. Krishna Moorthy
Abstract
This paper is concerned with the global asymptotic stability of the neutral type fractional‐order memristor‐based neural networks with leakage discrete and distributed delays. By building a sensible Lyapunov fractional related with integral and fractional derivative terms, a few satisfactory conditions comprehensively asymptotic stability is gotten. At that point, the global asymptotically stability investigation of fractional‐order neural systems utilizes the results from the obtained LMI conditions. Finally, numerical examples are provided to illustrate the effectiveness of the established of the proposed results.
Topics & Concepts
MathematicsExponential stabilityFractional calculusMemristorStability theoryControl theory (sociology)Artificial neural networkApplied mathematicsStability (learning theory)Type (biology)Term (time)Lyapunov functionEquilibrium pointMathematical analysisComputer scienceDifferential equationNonlinear systemControl (management)BiologyPhysicsArtificial intelligenceQuantum mechanicsEcologyMachine learningEngineeringElectrical engineeringNeural Networks Stability and Synchronizationstochastic dynamics and bifurcationAdvanced Memory and Neural Computing