This article investigates the secure consensus problem for nonlinear leader-following multiagent systems (MASs) under denial-of-service (DoS) attacks. First, an improved memory-based adaptive event-triggered mechanism (MAETM) is proposed to reduce data redundancy and save network resources. Unlike previous MAETMs, in order to effectively prevent excessively long data triggering periods or overly frequent triggering, the proposed MAETM introduces an upper limit and a lower limit to limit the threshold range. In this way, the communication resources can be effectively saved. In addition, considering the impact of DoS attacks, a new dynamic-memory-weight-dependent (DMW-dependent) security control protocol is proposed. Unlike control methods that use fixed weights, the protocol dynamically adjusts the weights of historically released packets according to DoS attacks, thus more fully utilizing the information of successfully transmitted packets to mitigate the impact of DoS attacks. Subsequently, sufficient conditions for the secure consensus of MASs are derived by constructing Lyapunov–Krasovskii functionals (LKFs) and using the law of large numbers and the Lagrange mean value theorem. Finally, two numerical simulations are provided to verify the effectiveness of the proposed MAETM and DMW-dependent security control protocol.

In this article, the resilient secure synchronization of complex networks (CNs) that are subject to denial-of-service (DoS) attacks is studied. In contrast to existing logic processors, a new processor in which more essential information on DoS attacks, such as the number of sampling instants being attacked and attack moment being detected, can be captured is designed. Based on the benefits of the logic processor, a switching sampled-data (SD) control protocol in which different feedback gains are chosen for different attack cases is proposed. In contrast to existing control schemes, the switching SD control protocol is more flexible. Subsequently, according to different attack cases, a switching Lyapunov-Krasovskii function (LKF) that can effectively fulfil the switching SD control protocol is founded. New resilient secure synchronization criteria that can successfully counteract the effects of DoS attacks are then established for CNs based on the switching SD control protocol and switching LKF. Finally, a complex Chua’s circuit system is used to give evidence of the feasibility and superiority of the proposed method.

In this article, a general approach to fixed-time synchronization problem is investigated for the general system of fractional-order multidimension-valued fuzzy memristive neural networks. First, we complete the establishment of the new model which is so general that we can regard it as fractional-order real-valued fuzzy memristive neural networks, fractional-order complex-valued fuzzy memristive neural networks, and fractional-order quaternion-valued fuzzy memristive neural networks. Then, we mainly apply two new general inequalities such as extended Cauchy–Schwarz inequality and generalized derivative of fractional-order absolute value function in order to realize the general analysis on the discussed problem. Owing to the two new lemmas, we can construct the general Lyapunov–Krasovskii functional with adjustable coefficients, design the nonlinear controllers with fuzzy gains, as well as acquire the flexible criteria with several useful factors. Particularly, the acquisition of the less conservative fixed time benefits from the new controllers which not only contains the common feedback gains but also can be comprised of the general coefficients and the fuzzy gains. Finally, a numerical example is provided to demonstrate our theoretical results.

The unified criteria are analyzed on the global dissipativity and stability for the delayed fractional-order systems of multidimension-valued memristive neural networks (FSMVMNNs) in this article. First, based on the comprehensive knowledge about multidimensional algebra, fractional derivatives, and nonsmooth analysis, we establish the unified model for the studied FSMVMNNs in order to propose a more uniform method to analyze the dynamic behaviors of multidimensional neural networks. Then, by mainly applying the Lyapunov method, employing several new lemmas, and solving some mathematical difficulties, without any separation, we acquire the unified and concise criteria. The derived criteria have many advantages in a smaller calculation, lower conservatism, more diversity, and higher flexibility. Finally, we provide two numerical examples to express the availability and improvements of the theoretical results.

This article is concerned with the problem of the global Mittag-Leffler synchronization and stability for fractional-order quaternion-valued neural networks (FOQVNNs). The systems of FOQVNNs, which contain either general activation functions or linear threshold ones, are successfully established. Meanwhile, two distinct methods, such as separation and nonseparation, have been employed to solve the transformation of the studied systems of FOQVNNs, which dissatisfy the commutativity of quaternion multiplication. Moreover, two novel inequalities are deduced based on the general parameters. Compared with the existing inequalities, the new inequalities have their unique superiorities because they can make full use of the additional parameters. Due to the Lyapunov theory, two novel Lyapunov-Krasovskii functionals (LKFs) can be easily constructed. The novelty of LKFs comes from a wider range of parameters, which can be involved in the construction of LKFs. Furthermore, mainly based on the new inequalities and LKFs, more multiple and more flexible criteria are efficiently obtained for the discussed problem. Finally, four numerical examples are given to demonstrate the related effectiveness and availability of the derived criteria.