Synchronization in finite-/fixed-time of delayed diffusive complex-valued neural networks with discontinuous activations

Adaptive Fuzzy Feedback Controller Design for Finite-Time Mittag-Leffler Synchronization of Fractional-Order Quaternion-Valued Reaction-Diffusion Fuzzy Molecular Modeling of Delayed Neural Networks

“…In the implementation, due to the restrictions of equipments and influence of the environment, the reactiondiffusion phenomenon and fuzzy rules in CVNNs. Different from the existing reaction-diffusion CVNNs and without T-S fuzzy rules in [60]- [62], reaction-diffusion CVNNs without fractional-order case in [60]- [62], and the T-S fuzzy fractional-order reaction-diffusion CVNNs is newly built in (10), ( 11) and ( 16), (17), which not only considers the effect of the reaction-diffusion phenomenon but the fuzzydependent adjustable matrix inequality technique is more flexible and helpful to reduce the conservatism and compared with integer-order neurons, fractional-order neurons are helpful for effective signal detection and extraction. Thus, compared with the models in [60]- [62], the model in (10), ( 11) and ( 16), ( 17) is more applicable.…”

“…Different from the existing reaction-diffusion CVNNs and without T-S fuzzy rules in [60]- [62], reaction-diffusion CVNNs without fractional-order case in [60]- [62], and the T-S fuzzy fractional-order reaction-diffusion CVNNs is newly built in (10), ( 11) and ( 16), (17), which not only considers the effect of the reaction-diffusion phenomenon but the fuzzydependent adjustable matrix inequality technique is more flexible and helpful to reduce the conservatism and compared with integer-order neurons, fractional-order neurons are helpful for effective signal detection and extraction. Thus, compared with the models in [60]- [62], the model in (10), ( 11) and ( 16), ( 17) is more applicable. T-S fuzzy FORD-DQVNNs can be regarded as a generalization of fractionalorder reaction-diffusion CVNNs, thus Theorem 1 and Theorem 2 can be used to estimate the FTMLS of T-S fuzzy fractional-order reaction-diffusion CVNNs.…”

“…Several corollaries are provided to show the advantages of the obtained results. It is noted that our results are comprehensive and include some existing ones [60]- [62] as special cases. (v) To further illustrate the effectiveness of our theoretical result approach is demonstrated by numerical example and from the simulation results to comparing control scenarios are given.…”

Synchronization of time invariant uncertain delayed neural networks in finite time via improved sliding mode control

“…It is worth noting that most of neural network applications involve complex signals, and hence the study of complex-valued neural networks is essential for many real-world devices [8][9][10][11][12][13][14][15][16]. For example, a single real-valued neuron cannot deal with the problems in the detection of symmetry and XOR problems, but a single complex-valued neuron with orthogonal decision boundaries can successfully deal with them.…”

Global Exponential Stability of a Delayed HIV Infection Model with a Nonlinear Incidence Rate

“…In fact, the known convergence rate means that the range of the population is predictable; that is to say, we can estimate the range of changes in the population within a given time range. In particular, since the exponential convergence rate reveals the variation range of population in different time periods, there have been extensive results on the problem of the exponential stability of epidemic models in the literature studies [25][26][27][28]. Now, a question naturally arises: under what conditions is the noninfected equilibrium (x * , y * , v * , z * ) � (x * (ρ), 0, 0, 0) of system (2) with initial conditions (3) are exponentially stable?…”