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This paper investigates the secure defense control problem for memristive recurrent neural networks (MRNNs) under denial-of-service (DoS) attacks. Based on quantizer and logical processor techniques, a new secure defense control strategy is designed to maintain the performance of MRNNs subject to DoS attacks. The secure defense control strategy can not only effectively capture information about the dwell time of each DoS attack, but also can effectively reduce the amount of data to be transmitted and save communication resources. By constructing a Lyapunov–Krasovskii functional that depends on sampled information at t k and t k + 1 , some new stability criteria are derived for MRNNs under DoS attacks. By solving a set of LMIs, the control gain of the quantized sampled-data controller can be obtained. Thus, the corresponding secure quantized sampled-data controller is designed for MRNNs under DoS attacks. When there is no quantizer, the secure defense control problem for MRNNs under DoS attacks is also studied. Two numerical examples are given to confirm the effectiveness of the main results. [ABSTRACT FROM AUTHOR]

This paper is dedicated to dealing with the sampled measurement-based robust impulsive filter design problem for delayed Lur'e implicit hybrid systems via free-weighting matrix approach. Stochastic admissibility and H ∞ performance index for the implicit impulsive filtering error system are ensured based on a holistic impulse-time-dependent Lyapunov–Krasovskii functional, which embodies the impulse instants, time-varying delays and Markovian jump modes. The effect of sampled measurement output on the impulsive filter is considered, where the sampling moments are corresponding to the impulse instants. By applying the improved free-weighting matrix technique, the derivative of time-varying delay in implicit system states is no longer subject to the least upper bound 1. A set of linear matrix inequalities are applied to construe designing criterion for the desired mode-dependent implicit impulsive filter. The practicality of the developed approach is verified by nonlinear RC circuit. [ABSTRACT FROM AUTHOR]

This article considers the event-based security control problem for an interconnected system with Markovian switching topologies, where the Markovian process governs the switching of the communication topologies. Considering the effect of transmission constraints on control design, a Bernoulli-distributed variable is utilized to formulate the random network attacks. A sampling-data-based event-triggered communication mechanism is presented to decrease unnecessary transmission, where the average data-releasing rate can be decreased greatly. Considering the effects of deception attacks and event-triggered mechanism simultaneously, an observer-based switched control system model is established. By combining this new model and employing the proper Lyapunov–Krasovskii functional, some sufficient criterions are derived such that the closed-loop error system is exponentially mean-square stable with the desired disturbance attenuation, and the controller and observer gain matrices will be tackled simultaneously via the solution of linear matrix inequalities. Finally, this article employs a simulation example to verify the availability of proposed methods. [ABSTRACT FROM AUTHOR]