Govindasamy Narayanan

TL;DR: Using Lyapunov function and Homomorphic mapping theorem, sufficient conditions for the existence of unique equilibrium and global asymptotic stability of complex-valued systems are derived and Mittag-Leffler stability for BAM neural networks(BAMNNs) have been proposed when the nonlinear complex activation functions are bounded.

TL;DR: Using the Lyapunov theory, differential inclusion theory, and fractional calculus theory, finite-time stabilization condition for fractional-order memristive complex-valued BAM neural networks and the upper bound of the settling time for stabilization are obtained.

TL;DR: The impulsive effects on the stability equilibrium solution for Riemann–Liouville fractional-order fuzzy BAM neural networks with time delay are investigated and the existence and uniqueness of the equilibrium point of the system are analyzed.

TL;DR: By employing the ideas of Cauchy–Schwartz inequality, Burkholder–Davis–Gundy inequality, analysis technique, some sufficient conditions are derived to ensure the uniform stability in mean square of stochastic fractional-order memristor fuzzy BAM neural networks.

TL;DR: In this paper, the authors investigated finite-time stability analysis of fractional-order memristive fuzzy cellular neural networks (MFFCNNs) with time delay and leakage term.