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TOC Alert for Publication# 6221021 2019September05<![CDATA[Table of contents]]>499C1C1445<![CDATA[IEEE Transactions on Systems, Man, and Cybernetics publication information]]>499C2C273<![CDATA[An Event-Based Asynchronous Approach to Markov Jump Systems With Hidden Mode Detections and Missing Measurements]]>∞ control for a class of networked Markov jump systems (MJSs) with missing measurements. The phenomenon of asynchronism occurs in both the controller and the actuator-failure model, which is estimated by the hidden Markov model, is taken into consideration. In addition, to reduce the burden of data transmission, a mode-dependent event-triggered mechanism (ETM) is proposed. Together with ETM, a network-induced delay is introduced. Subsequently, to guarantee that the MJS is stochastically stable, an event-based asynchronous controller is designed. Finally, to reveal the effectiveness of the proposed method, a simulation example of pulse width-modulation-driven boost converter is considered.]]>49917491758904<![CDATA[Cooperative Adaptive Event-Triggered Control for Multiagent Systems With Actuator Failures]]>499175917681534<![CDATA[Robust Simultaneous Fault Estimation and Nonfragile Output Feedback Fault-Tolerant Control for Markovian Jump Systems]]>49917691776693<![CDATA[Fuzzy Adaptive Distributed Event-Triggered Consensus Control of Uncertain Nonlinear Multiagent Systems]]>499177717861716<![CDATA[Memristor-Based Echo State Network With Online Least Mean Square]]>499178717962613<![CDATA[Fault-Tolerant Resilient Control For Fuzzy Fractional Order Systems]]>499179718051060<![CDATA[Deep Convolutional Neural Networks for Human Action Recognition Using Depth Maps and Postures]]>499180618192859<![CDATA[Adaptive Neural Backstepping Control Design for A Class of Nonsmooth Nonlinear Systems]]>499182018311379<![CDATA[A Novel Method for Detecting New Overlapping Community in Complex Evolving Networks]]>${F}$ -score, and can also predict an overlapping community’s future considering node evolution, activeness, and multiscaling. This paper presents a novel method based on node vitality, an extension of node fitness for modeling network evolution constrained by multiscaling and preferential attachment. First, according to a node’s dynamics such as link creation and destruction, we find node vitality by comparing consecutive network snapshots. Then, we combine it with the fitness function to obtain a new objective function. Next, by optimizing the objective function, we expand maximal cliques, reassign overlapping nodes, and find the overlapping community that matches not only the current network but also the future version of the network. Through experiments, we show that its NMI and ${F}$ -score exceed those of the state-of-the-art methods under diverse conditions of overlaps and connection densities. We also validate the effectiveness of node vitality for modeling a node’s evolution. Finally, we show how to detect an overlapping community in a real-world evolving network.]]>49918321844899<![CDATA[Adaptive Finite Time Control of Nonlinear Systems Under Time-Varying Actuator Failures]]>499184518521108<![CDATA[Nonlinear Stochastic Attitude Filters on the Special Orthogonal Group 3: Ito and Stratonovich]]>499185318651658<![CDATA[Event-Triggered Optimal Neuro-Controller Design With Reinforcement Learning for Unknown Nonlinear Systems]]>499186618781295<![CDATA[Planning and Operation of Parking Lots Considering System, Traffic, and Drivers Behavioral Model]]>499187918922635<![CDATA[Observer-Based Adaptive Consensus for a Class of Nonlinear Multiagent Systems]]>49918931900836<![CDATA[Quantized <inline-formula> <tex-math notation="LaTeX">$H_infty$ </tex-math></inline-formula> Output Control of Linear Markov Jump Systems in Finite Frequency Domain]]>${H_infty }$ static output control of linear Markov jump systems. The output quantization is transformed into a sector bound form, and the finite frequency performance is handled by Parseval’s theorem. With the aid of Finsler’s lemma, sufficient conditions for the resulting closed-loop system are first established to satisfy the required finite frequency performance. To treat the static output feedback control problem in the framework of linear matrix inequalities, a new strategy is developed to decompose the coupling among Lyapunov variables, controller gain, and system matrices. In contrast to the existing results in the literature, no additional assumptions are imposed on the system matrices. Numerical examples are presented to demonstrate the validity of the established results.]]>49919011911962<![CDATA[Global Stabilization of a Class of Switched Nonlinear Systems Under Sampled-Data Control]]>49919121919828<![CDATA[Introducing IEEE Collabratec]]>499192019202096<![CDATA[IEEE Systems, Man, and Cybernetics Society Information]]>499C3C3110<![CDATA[Information For Authors]]>499C4C4109