Delay-dependent robust asymptotic state estimation of Takagi–Sugeno fuzzy Hopfield neural networks with mixed interval time-varying delays

Finite-timeH∞synchronization control for semi-Markov jump delayed neural networks with randomly occurring uncertainties

“…where y (t) and f (y (t)) have the similar definition as x (t) and f (x (t)) in (2), and u (t) ∈ R s is the appropriate control input that will be designed in order to obtain a certain control objective. E i is a known real constant matrix for every i ∈ S; ω (t) ∈ R q is the disturbance input that belongs to L 2 [0, ∞) and satisfies…”

“…Thus, the dynamical behaviors of DNNs have attracted a great deal of attentions and many significant advances have been reported in the literature; see, e.g. [2,3,4,5,6], and the reference therein.…”

Design of state estimator for bidirectional associative memory neural networks with leakage delays

“…It is well known that the time delays are caused by signal transmission, signal processing and propagation which may induce oscillation, divergence, and instability in the network behavior. During the last decade, the stability analysis of neural networks with time delays has been receiving more attention and many significant results have been obtained in the literature (see [1,3,9] and the references therein). Matrix measure strategies for stability and synchronization of inertial BAM neural network with time delays have been proposed in [7].…”

LMI-Based Stability Criterion of Impulsive T-S Fuzzy Dynamic Equations via Fixed Point Theory

“…Besides, the contraction-mapping theory is also an important fixed point theory in studying the stability of dynamics equations (see, e.g., [11,33,[39][40][41][42]). On the other hand, fuzzy logic theory has shown to be an appealing and efficient approach to dealing with the analysis and synthesis problems for complex nonlinear system [20][21][22][23][24][25]. In practice, the fuzzy model is far more important than stochastic model.…”