Mean-square exponential stability of stochastic inertial neural networks

Mean-square exponential input-to-state stability of stochastic inertial neural networks

“…Although Wang and Chen [43] have studied the mean-square exponential stability of stochastic inertial neural network (1.4) with two groups of different initial conditions (1.2), it is not appropriate to mean-square exponentially input-to-state stability. Fortunately, motivated by Zhu and Cao [38], who introduced the definition of the mean-square exponential input-to-state stability for stochastic delayed neural networks, together with the mean-square exponential stability (Wang and Chen [43]), we present the following definition.…”

Robustness analysis of exponential stability of fuzzy inertial neural networks

“…Definition 2. [38] SFDINN (20) is said to be mean square exponentially stable if there are two constants ℓ > 0, ℘ > 0 such that…”

“…In [22], Cui et al obtained stability criteria for DINN with random pulses by using matrix measurement method as well as stochastic theory. Wang and Chen studied the mean-square exponential stability of delayed SINNs (DSINNs) by constructing Lyapunov-Krasovskii functionals in [23].…”

“…• Compared with [26,27], this paper further considers the influence of inertia term in the FNN model, inertia term can better describe the relationship between current and flux. Compared with [20][21][22][23], fuzzy logic is considered in this paper, it improves the ability to handle the fuzziness in simulations.…”

“…(22) and(23), we can obtain the following two transcendental Equations 5 π2 exp(0.3Λ 3 ) + exp(−0.24)…”