In this paper, the almost sure synchronization of stochastic multi-layer networks with noise coupling is studied by means of pinning intermittent volatile event-triggered control. During the control interval, the determination of control updates follows an event-triggered mechanism with waiting time, which avoids continuous monitoring and also eliminates Zeno behavior. In contrast to the existing literature that focuses on moment synchronization, we study almost sure synchronization on stochastic multi-layer networks, where noise coupling with time-varying and nonlinear features plays an active role. In addition, the control gain displays sign-indefinite characteristics that follow some volatility patterns, including synchronizing control and desynchronizing inputs. A concept of average volatile control gain is presented to quantify the control gain. To cope with the challenges posed by volatile gain and intermittent control input, a generalization of Halanay-type inequality is proposed, its coefficients are time-varying and piecewise continuous, which shows that the results have a wider range of applications. Based on the stochastic analysis technique, graph theory, and Lyapunov method, the synchronization criteria are established. Finally, the feasibility is illustrated by simulation examples. Note to Practitioners—This paper was motivated by existing results on pinning intermittent control and event-triggered control about almost sure synchronization. The existing results mainly require that the control signals were updated in a consecutive manner during control activation intervals, which may hardly be implemented on digital computers. This paper designs a novel hybrid control method named pinning intermittent volatile event-triggered control, and therefore, the proposed approach is more friendly for control engineers. In addition, the volatile control gain is considered. The results obtained are applied to a spring-mass-damper system, demonstrating their effectiveness and it is expected that the proposed approach can be extended to more practical physical engineering systems.

This paper focuses on the exponential stability of time-varying hybrid stochastic large-scale networks, in which a novel discrete-time observation control strategy with volatile control gain is imposed. The control gain exhibits sign-indefinite characteristics that follow certain volatile patterns. Then, the strategy can preferably respond to extrinsic perturbances and defend actuators and facilities by comparison with the position in constant gain. To quantify the volatile control gain, a concept of average volatile discrete-time observation control gain is proposed. In light of stochastic analysis theory and Lyapunov method, we establish improved stability criteria. In contrast to earlier results, the piecewise continuous, time-varying, and indefinite functions replace the constant coefficient of the upper bound estimation for the operator of the Lyapunov function, i.e., it can be positive or negative along time evolution, which shows wider applications of our results. Furthermore, considering the phenomenon of controller failure and packet losses, obtained results are applicable for analyzing the stabilization via intermittent discrete-time observation control and nonuniform discrete-time observation control, respectively. Finally, two applications to oscillator systems and single-link robot arms are presented and numerical simulations are exploited to illustrate the feasibility. Note to Practitioners—This paper is motivated by existing results on discrete-time observation control for the dynamics of hybrid stochastic large-scale networks. The existing results mainly require continuous updates to the control signals while maintaining a constant control gain. This is challenging to achieve on digital computers and often does not effectively respond to external disturbances. This paper designs a new hybrid control called volatile discrete-time observation control, and a concept of the control gain is proposed to quantify the volatile control gain. Specifically, the obtained results also apply to scenarios involving control failures and packet loss. The results are applied to oscillator systems and single-link robot arms, demonstrating their effectiveness and it is expected that the proposed approach can be extended to more practical physical engineering systems.

This article studies exponential synchronization of complex networks under deception attacks via event-triggered impulsive control. A new event-triggered mechanism is proposed to avoid Zeno behavior based on the topology of the networks and the Lyapunov function of the subsystem. Using a combination of the Lyapunov method and graph theory, several criteria for synchronization of complex networks under attacks are given, which are related to the event-triggered parameters, the topology of the network, and the attack signal sent by enemies. Given the prevalence of delays, we also extend the obtained results to delayed deception attacks, where malicious attackers modify state data from past moments. Finally, the theory applies to circuit systems under deception attacks and delayed deception attacks, respectively, and numerical simulations are given to verify the effectiveness and practicality of our results.

Directional Antennas have drawn some attention in flying ad-hoc networks (FANET). Most of the existing works consider only beam steering in a 2-dimensional plane. However, when the networks scale up to a coverage of hundreds of kilometers, some challenges emerge for the 2D methods. In this paper, we design a 3D beam scanning pattern and propose an efficient scanning strategy for the neighbor discovery process based on the analysis regarding the distance between nodes as well as the earth's curvature. Also, we fine-tune the pitch angle of the beam according to the scanner's altitude. Simulation results show that the proposed scheme outperforms the conventional scheme in terms of neighbor discovery time.

This article investigates the stabilization of discrete-time stochastic neural networks with time-varying delay via aperiodically intermittent control (AIC). A comprehensive analysis of the stabilization of discrete-time delayed systems via AIC is provided, where the Lyapunov function method and the Lyapunov-Krasovskii functional method are investigated, respectively. Then, three stabilization criteria are given, which extend previous works from the continuous-time framework to the discrete-time one, and the average activation time ratio (AATR) of AIC is estimated. It is highlighted that for the Lyapunov-Krasovskii functional method, a more flexible estimation for the AATR can be obtained. Finally, the differences and the advantages of the three stabilization criteria are illustrated by numerical simulations.

This article is concerned with the stability analysis of time-varying hybrid stochastic delayed systems (HSDSs), also known as stochastic delayed systems with Markovian switching. Several easy-to-check and less conservative Lyapunov-based sufficient criteria are derived for ensuring the stability of studied systems, where the upper bound estimation for the diffusion operator of the Lyapunov function is time-varying, piecewise continuous, and indefinite. It should be stressed that our results can be directly used to analyze the stabilization of HSDSs via aperiodically intermittent control (AIC). Compared with the existing results about AIC, the restrictions on the bound of each control/rest width and the maximum proportion of rest width in each control period are removed. Thus, the conservativeness is reduced. Finally, two examples, together with their numerical simulations, are provided to demonstrate the theoretical results.

This paper is concerned with the almost sure exponential synchronization of a multilayer network which is set up on a non-strongly connected digraph that can be classified into several layers by Tarjan's algorithm. Note that, in the multilayer network, white-noise-based time-varying coupling and drift term coupling are proposed to simulate two kinds of coexisting distinguishable interactions between vertices. We develop a normal analytical framework for studying synchronization of the multilayer network. Firstly, via aperiodically intermittent pinning noises, synchronization of vertices situated on the first layer is achieved in the layered network. Secondly, under the impact of the white-noise-based time-varying coupling in diffusion term, synchronization of the vertices located in other layer networks is developed with the support of synchronization for the pinned vertices. Employing Lyapunov method, graph theory and stochastic analysis technique, a criterion of almost sure global exponential synchronization is obtained. By adopting the concepts of average noise control rate and average noise control period proposed recently, we lessen the conservativeness of the conditions restricted on aperiodically intermittent noise control to optimize our results. Furthermore, an application to a class of Chua's circuits is exhibited in detail. In the end, we provide a numerical example to verify the validity of the theoretical results.

This paper concerns the stabilization problem of stochastic uncertain complex-valued delayed networks (SUCVDNs) via aperiodically intermittent nonlinear control. It is worth noting that the intermittent control is aperiodic and nonlinear. As a special case, when each control width tends to zero, intermittent control becomes impulsive control. Hence, the stabilization problem of SUCVDNs via impulsive control is also studied. The main method is the combination of the Lyapunov method and Kirchhoff’s matrix tree theorem in graph theory, which does not require us to solve any linear matrix inequalities. Different from previous results on complex-valued system, we consider the complex-valued system on complex space directly by using complex version Itô’s formula and (conjugate)${\mathbb {R}}$derivative. Then we give some sufficient criteria, which have a close relationship with the control interval and the topological structure of the considered network. The main results are applied to a class of stochastic complex-valued coupled oscillators, and numerical examples are also presented to show the effectiveness of the control strategies.

An iterative alternating direction method of multipliers (ADMM) is proposed for inverse finite-element–boundary-integral (FE–BI) problem with total variation (TV) regularization. The inverse FE–BI fits to a wide class of penetrable sensing applications, where this study specifically targets the problem of radio tomography of asteroid interior structure using orbiting spacecraft. The TV regularizer enforces sparsity on the gradient of reconstructed permittivity, which agrees well with the “piecewise constant” reality of “rocks embedded in soil” scenario and, meanwhile, addresses the inherent ill-posedness. For large-scale asteroid problems, the distributed ADMM algorithm is adapted to solve the linear TV inversion at each iteration. The 2-D inversion is validated with the Fresnel Institute measurement data. Simulated cases of asteroid internal imaging are also presented. The proposed iterative ADMM can be also applied to similar penetrable imaging applications.

This paper presents a comparative study of two receiver schemes for interleaved OFDMA uplink. In the first scheme, called the post-DFT processing based interference cancellation receiver, the CFOs are compensated in frequency domain and an iterative interference-cancellation scheme is used to reduce the inter carrier interference (ICI) and/or multiuser interference (MUI). The other scheme, the signal structure-based MMSE receiver, exploits the signal inner structure on the interleaved OFDMA uplink and separates single user signal waveform by compensates the effective carrier frequency offsets. Simulation results show that the signal structure-based MMSE receiver is robust to large CFOs but its computation complexity increases considerably with the number of users. Furthermore, it assumes to know the signal power. When the CFOs are small, the post-DFT processing based interference cancellation receiver is preferable because its computation is easy with the number of users and it needs not know signal power

In this paper, we propose a zero correlation zone (ZCZ) sequences-based carrier frequency offset estimation algorithm for interleaved OFDMA uplink. By introducing the effective carrier frequency offset (CFO) and designing an appropriate training sequence for each user, we propose a training sequence-based CFO estimation algorithm thus avoiding the computationally complex subspace-based method proposed by Cao & Tureli (2002). Zero correlation zone sequence set is used as training sequence to mitigate multipath inference and multiuser inference. Simulation results show that the proposed algorithm is effective in multi-path fading channel