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This study proposes a novel tool for neural network modeling by integrating quaternion theory, discrete fractional calculus, and stochastic analysis, thereby introducing a stochastic discrete fractional delayed quaternion-valued neural network model. Firstly, we prove the existence and uniqueness of the equilibrium point for the model by using the homeomorphism mapping theory. Secondly, we give some new inequalities in the quaternion domain. Through these inequalities and Lyapunov theory, we establish sufficient linear matrix inequality (LMI) conditions on the global mean square stability and global mean square Mittag-Leffler stability for the model. Furthermore, the linear feedback control approach is employed to derive sufficient LMI conditions that achieve the model's global mean square synchronization and global mean square Mittag-Leffler synchronization. Finally, several numerical examples validate the findings obtained. [ABSTRACT FROM AUTHOR]

This paper presents a study on the predefined-time (PdT) and practical PdT synchronization of competitive neural networks (CNN) in the presence of different time scales and external disturbances. Two types of external disturbances, which satisfy Lipschitz or bounded conditions, are investigated respectively. The new PdT and practical PdT stability theorems are derived in singularly perturbed systems, where the final residual set is given in detail. By employing the newly derived stability theorems, novel autonomous controllers are designed without relying on a continuous linear term and time scale parameters, while enabling PdT or practical PdT synchronization for drive-response CNNs. Additionally, upper bounds for the settling time are estimated, allowing for adjusting the predefined synchronization times regardless of the initial conditions. Finally, numerical simulations are conducted to demonstrate the effectiveness of the main results. [ABSTRACT FROM AUTHOR]

This paper proposes a novel time-dependent gain parameter-based sliding mode controller (SMC) to realize the finite-time/fixed-time synchronization of memristive shunting inhibitory cellular neural networks (Mem-SICNNs) having time-varying delays. In this regard, a new terminal sliding mode surface is designed and its reachability is analyzed. According to synchronization error analysis, the stability property of the desired error system is reached within finite-time/fixed-time range by proposing a unique time-dependent gain parameter-based SMC and choosing the appropriate Lyapunov functionals. Finally, a numerical example is approached by software simulation and manual calculation to estimate the settling-time of the finite-time/fixed-time synchronization criteria of the proposed Mem-SICNNs model. [ABSTRACT FROM AUTHOR]

This article provides a comprehensive overview of the role and responsibilities of liaison officers (LNOs) in the military. LNOs act as representatives of commanders and facilitate communication between different commands. They play a crucial role in monitoring operations, coordinating between organizations, and providing assistance as needed. The article emphasizes the importance of qualities such as access, relationships, presence, credibility, dependability, and personality for LNOs to be effective in their roles. It offers practical advice and lessons learned for LNOs to succeed and make a meaningful impact in their positions. [Extracted from the article]

The fractional competitive neural networks (FCNNs) with multiple restrictions are considered in this article. Specially, the FCNNs with memristors and time-varying delays in complex field (FCMCNNs) are first introduced, as well as the asymptotic stability (AS) and quantitative synchronization (QTS) issues are investigated. Firstly, applying Filippov's conclusion theory, a model of FCMCNNs is reduced to a simpler one containing the time-switching memristive coefficients. Secondly, in virtue of the Banach fixed-point theorem, the AS is sufficiently discussed. Thirdly, in the light of the quantized controller (QTC), some concise inequality criteria are drawn to attain the QTS of the master–slave systems. Lastly, by providing two simulation examples, the results obtained manifest the availability and practicality. [ABSTRACT FROM AUTHOR]

The finite-time synchronization and topology identification problems of stochastic multi-layer networks with Markovian switching are investigated in this paper. Compared with previous studies, Markovian switching is considered in stochastic multi-layer networks. First, by using Kirchhoff's matrix tree theorem in graph theory, the Lyapunov function of the coupling system is constructed indirectly from the Lyapunov function of the vertex system. In view of finite-time stability theory and stochastic analysis technique, some finite-time synchronization criteria of stochastic multi-layer networks are proposed. Moreover, the intra-layer and inter-layer topological structures are successfully identified in finite time. Then, using the pinning control technique, the unknown partial topological structures are also identified in finite time. In the end, two examples for whole and partial topology identification of two-layer small-world networks are given. [ABSTRACT FROM AUTHOR]

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This paper introduces the signed graph into fractional-order coupled neural networks (FCNNs) and the bipartite synchronization is investigated for leaderless FCNNs. Instead of formulating leader's state or isolated node's state as the synchronization reference target, the bipartite synchronization of leaderless FCNNs is discussed by developing a direct error approach. First, an important fractional-order inequality is rigorously proved by contradiction. By virtue of fractional-order inequality, gauge transformation and several analytical tools, the criteria of bipartite leaderless synchronization are obtained for FCNNs with heterogeneous and homogeneous coupling weights. Specially, for the two types coupling weights, the adaptive pinning schemes are adopted which just rely on partial network information based on the spanning tree and connected dominating set, respectively. Eventually, the theoretical analysis is verified by two numerical simulations. [ABSTRACT FROM AUTHOR]

This paper delves into the robust H ∞ synchronization for diffusion-type parabolic complex networks (PCNs) characterized by second-order nonlinear partial differential equations (PDEs). Given that the potential deterioration of network performance or the loss of network synchronization caused by external disturbances and time delays, the analysis and synthesis results for the robust H ∞ synchronization of the PCNs with coupling time-varying delays are derived with and without the utilization of the distributed adaptive state feedback control protocol. A numerical example is employed to validate the effectiveness of the acquired H ∞ synchronization results and the adaptive protocol. [ABSTRACT FROM AUTHOR]

In this paper, the finite-time and fixed-time synchronization problems of multi-layer networks are studied. In order to achieve the synchronization, two novel switching controllers are proposed and the effectiveness is verified by the Lyapunov stability theory. Moreover, the upper bound of time and energy costs are estimated. Specifically, the results show that increasing the synchronization speed will inevitably increase the consumption of control energy, which means there is a trade-off between time and energy costs. Therefore, an index function is given to quantify the time and energy costs, and it is found that adjusting the parameters can minimize the total cost. Finally, the theoretical results are verified by some numerical simulations. [ABSTRACT FROM AUTHOR]

Different from the majority of existing results that focus on the passivity analysis of nonlinear systems, this paper attempts to analyze the more general QSR-dissipativity of fractional-order neural networks that own output coupling and multiple coupled weights, where outer coupling weights can be adjusted online by developing an adaptation law. Using the linear matrix inequality technique, several sufficient criteria that not only guarantee the QSR-dissipativity of the network system but also achieve global synchronization even under zero input are established. Of particular significance is the proposal of a fractional Lyapunov-like lemma, which plays a crucial role in verifying the asymptotic stability of synchronization errors. Finally, a simulation example is presented to verify the plausibility of the theoretical results. [ABSTRACT FROM AUTHOR]

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This article addresses the almost surely global exponential synchronization (ASGES) for complex networks in the delay-partitioning framework. Under impulsive control, by dividing impulse intervals and time delay, the information of the impulse intervals can be more fully utilized. Firstly, a novel type of Lyapunov functional is introduced by applying a practical switching law, which combines mode-dependent average dwell-time (MDADT) and transition probability (TP). The use of the partition method makes the relationship between the undelayed state and the delayed state can be better handled, delay-dependent stability criteria are established with less conservatism. Secondly, under the action of impulsive control and fault-tolerant control, a controller synthesis algorithm is provided. Moreover, a corollary extends the results to intermittent control. Finally, an example of Chua's circuit networks is provided to illustrate the effectiveness of proposed method, which can obtain larger allowable time-delay. [ABSTRACT FROM AUTHOR]

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The current study is concerned with the dynamical investigation, synchronization, and engineering application of a new variable-order fractional neural network. The model of the variable-order fractional neural network is presented, and its chaotic behavior is studied through well-known dynamical tools. Then, a new control technique is proposed for the control of the system. Although finite-time estimators considerably enhance the performance of controllers, studies that offer finite-time estimators for the control of fractional-order systems are rare in the literature. Motivated by this, as a novel approach, the proposed control technique is equipped with a finite-time estimator, which is able to approximate highly nonlinear disturbances and uncertainties. The stability and finite-time convergence of the sliding surface and error dynamics based on the proposed control technique are proven. Through numerical simulations, the effectiveness of the designed control scheme in the presence of complex time-varying disturbances is illustrated. Then, a voice encryption application has been implemented in order to show the feasibility of data security applications of the proposed variable-order neural network. Finally, to investigate the effectiveness of the implemented data security application, the entropy values for original, encrypted, and decrypted voice data are presented. Numerical analyses of encryption clearly confirm that encryption is done securely and there is no corruption or data loss in encryption and decryption processes. [ABSTRACT FROM AUTHOR]

Copyright of PC Welt Plus is the property of IDG Communications, Inc. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Digital Production is the property of Busch Glatz Germany GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper aims to investigate the global and exponential cluster synchronization issue for one class of complex networks with non-identical nodes and hybrid time-varying delays by proposing a novel region-division event-triggered aperiodically intermittent pinning controller. The relationship between the three subregions with non-negative real regions and the auxiliary function in the event-triggered mechanism determines whether the controller is activated or not. It should be noticed that the exponential convergence rate of synchronization can be predesigned. Sufficient conditions for the realization of the cluster synchronization are obtained globally and exponentially based on the aperiodically intermittent pinning strategy, the region-division event-triggered mechanism and the segmentation analysis method. Furthermore, the Zeno behavior is successfully excluded. Finally, the effectiveness of the proposed theorem and control strategy is verified by a simulation example. [ABSTRACT FROM AUTHOR]

In this paper, in order to obtain a smaller estimation of settling time, reduce chattering caused by sign function and improve network communication efficiency, the fixed-time (FXT) synchronization of delayed BAM neural networks is analyzed based on some new FXT stability results and non-chattering quantized controllers. Firstly, by comprehensively discussing the conditions of power laws in differential inequalities, a new FXT stability lemma is presented and a smaller upper bound of settling time is estimated. Then, unlike previous controllers with sign functions, a non-chattering quantized state feedback control and a non-chattering quantized pinning control are designed, and some sufficient conditions are derived to ensure FXT synchronization of the established system. Finally, two numerical simulations are given to verify the effectiveness of the theoretical results. The results show that compared with the previous researches, this paper provides a smaller upper bound. However, the convergence time of the uncontrolled nodes is indirectly affected by the coupling of the controlled nodes and is much longer than the estimated upper bound. [ABSTRACT FROM AUTHOR]

This article aims to study fixed-time projective lag synchronization(FXPLS) and preassigned-time projective lag synchronization(PTPLS) of hybrid inertial neural networks(HINNs) with state-switched and discontinuous activation functions(DAFs). By constructing new hybrid fixed-time control and based on theory of non-smooth analysis, we achieve novel results on FXPLS for such HINNs. Through designing novel hybrid preassigned-time control, new criteria on PTPLS of the HINNs is also taken into account. And as distinct from recent works, the FXPLS and PTPLS results are established via non-variable substitution and in a more generalized framework than common synchronization, which also has more extensive practical applications. Finally, example simulations are displayed to set forth the validity of the acquired FXPLS and PTPLS. [ABSTRACT FROM AUTHOR]

The article focuses on the intersection of psychodermatology and skincare, highlighting how cosmetics are increasingly seen as part of a broader approach to improving mental health and well-being. It discusses the relationship between skin health, wellness and psychodermatology, emphasizing the importance of understanding the impact of psychological factors on skin conditions and vice versa.

Copyright of IEE: Industrie, Engineering, Effizienz is the property of Dokumentations- und Informationszentrum (DIZ) Munchen GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, the secure synchronization control problem of a class of complex time-delay dynamic networks (CTDDNs) under denial of service (DoS) attacks is studied. Based on the pinning control strategy, a non-fragile sampling controller is designed for a small number of nodes in the complex network. It can effectively solve the problem of limited communication resources and has good anti-interference performance. In order to resist the influence of DoS attacks, an improved comparator algorithm is designed to obtain the specific information of DoS attacks, including the upper and lower bounds of the DoS attacks duration, the DoS attacks frequency and the specific active/sleeping interval of DoS attacks. Based on Lyapunov stability theory and by designing the pinning non-fragile sampling controller, new security synchronization criteria are established for CTDDNs. Finally, two numerical examples are given to verify the validity of the theories. [ABSTRACT FROM AUTHOR]

This paper addresses the finite-time synchronization problem of complex networks under a new communication constraint. The situation that some communication channels used to transmit sub-information between two nodes may fail is considered, which causes the receiving node to be unable to obtain complete state information. Moreover, due to less information transmission between nodes, the analysis of finite-time synchronization problem becomes more difficult. Therefore, several questions naturally arise here: Under this communication restriction, how to remodel the complex network, and can the network achieve finite-time synchronization? To better solve these questions, the complex network model with partial communication channels failure is established first. Then, based on the finite-time stability theory and state layered method, two finite-time synchronization criteria for complex networks are provided. Finally, the effectiveness of obtained results are verified by numerical simulations. [ABSTRACT FROM AUTHOR]

Copyright of China Pulp & Paper Industry is the property of China Pulp & Paper Industry Publishing House and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

This paper discusses the synchronization results like robust exponential synchronization (RES) and exponential synchronization (ES) of uncertain infinite time-varying flexible delayed impulsive neural networks with and without distributed delay. First, we introduced a new lemma based on fundamental solution matrix for solving nonlinear neural networks by utilizing average impulsive interval (AII) and average impulsive delay (AID). Further, we examined some novel RES and ES results for proposed neural networks via the method of variation of constants. Finally, numerical examples are given to validate the proposed results, and the effectiveness of flexible delayed impulsive control is demonstrated using graphical representations. [ABSTRACT FROM AUTHOR]

Copyright of Digital Production is the property of Busch Glatz Germany GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Digital Production is the property of Busch Glatz Germany GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

We study synchronization phenomena in complex networks in terms of machine learning oscillators without conventional dynamical equations. Specifically, we adopt an effective machine learning technique known as reservoir computing for modeling dynamical systems of interest. By constructing a coupled configuration, we show that a collection of coupled reservoir oscillators are in identical synchrony over a wider window of coupling strengths. We find that the geometrical and dynamical properties of synchronous orbits are in excellent agreement with that of the learned dynamical system. Remarkably, through this synchronization scheme, we successfully recover an almost identical bifurcation behavior of an observed system via merely its chaotic dynamics. Our work provides an alternative framework for studying synchronization phenomena in nature when only observed data are available. • We study synchronization phenomena in complex networks in terms of machine learning oscillators. • We design a coupled configuration for achieving a collection of coupled reservoir oscillators. • We find that the geometrical and dynamical properties of synchronous orbits match that of a learned dynamical system. • We recover an almost identical bifurcation behavior of an observed system via only its chaotic information. [ABSTRACT FROM AUTHOR]

The article discusses technological advancements in the US Army, which require how a commander approaches the operations process and integrates novel solutions to tackle the situation. The civilian technologies such as commercial satellite connections and fifth-generation networks have helped improve connectivity and shortened latency. Distributed command and control for the Army of 2040 should be viewed as connected and synchronized nodes from home station to the battlefield.

• A class of more general link attacks with multiple patterns is considered. • A SETCM is proposed to reduce coupling communication burden and save coupling resources. • The security synchronization criteria under link attacks with multiple patterns are derived. This paper concentrates on the secure synchronization problem against link attacks in complex networks with event-triggered coupling. The link attacks for each link are independent, which means that there are multiple attack patterns for coupling communication topology. Then, the relevant model of link attacks with multiple patterns is constructed to analyze the effect on synchronization error system. Furthermore, to reduce communication burden and save coupling resources, a sampled-data-based event-triggered coupling mechanism is established. In this situation, the triggering condition is supervised only at discrete sampling instants. By employing Lyapunov theory and some inequality techniques, sufficient conditions are given to guarantee the synchronization against link attacks with multiple patterns. At last, a simulation example on Chua's circuit network is provided to demonstrate the effectiveness of the proposed results. [ABSTRACT FROM AUTHOR]

Multiplex networks involve different types of synchronization due to their complex spatial structure. How to control multiplex networks to achieve different types of synchronization is an interesting topic. This paper considers the fixed-time synchronization of multiplex networks under sliding mode control (SMC). Firstly, for realizing three types of synchronization of multiplex networks in a fixed time, a unified sliding mode surface (SMS) is established. After that, based on the theory of SMC, a sliding mode controller (SMCr) which is more intelligent and has a simpler form than those in the existing literature is put forward for multiplex networks. It can not only guarantee the emergence of sliding mode motion, but also can realize three different kinds of synchronization by adjusting some parameters or even one parameter of the controller. Based on some theories of fixed-time stability, this paper deduces several sufficient conditions for the trajectories of the system to reach the preset SMS in a fixed time, and derives some sufficient conditions for multiplex networks to realize three different types of fixed-time synchronization. At the same time, the settling time which can reveal what factors determine the fixed-time synchronization in multiplex networks is obtained. Finally, in numerical simulations, different chaotic systems are set for each layer of multiplex networks to represent the nodes of different layers, which can prove that the theoretical results are practical and effective. [ABSTRACT FROM AUTHOR]

• A general proportional integral observer - based disturbance compensation framework is constructed, using the idea of two-degree-of-freedom design, to achieve compensation for local disturbances and state-consensus control of wireless sensor network systems. • A minimum variance controller based on LMI solving is designed to achieve state consensus control for the complex sensor networks. • The design of the disturbance compensation uses the idea of zero-pole optimization to achieve feedback disturbance rejection control for periodic disturbances, providing a new solution for the handling of periodic disturbances. [Display omitted] Precise time synchronization is an enabling technology for mission-critical time-sensitive Industrial Internet of Things (IIoT). However, the crystal oscillator clock which is widely used in IIoT may suffer from periodic disturbances caused by repetitive motion or periodic vibration. To improve the time synchronization of distributed nodes subject to periodic disturbances, this paper proposes a novel disturbance rejection framework, General-Proportional-Integral-Observer-based Disturbance Compensation (GPIO-DC), with the proof of stability, and combined with a 2-freedom control design strategy to optimize both the disturbance rejection and clock tracking performance. And the GPIO's unique feature of blocking zeros are fully exploited to reject the periodic disturbance at its frequencies and a zero-pole optimal design algorithm is given. With the disturbance being compensated, a disturbance-free minimum variance time synchronization protocol for a complex network is developed and optimized by using Linear Matrix Inequality (LMI) to minimize the variance of networked synchronization errors. The performance of the proposed method is devalued by intensive simulation. Comparing with recent relevant research, the proposed method achieves a better performance in disturbance rejection and minimum variance. [ABSTRACT FROM AUTHOR]

This article addresses the approximate synchronization problem of two coupled multi-valued logical networks, including global and local cases. Three new notions: approximate synchronization state set (ASSS), the maximum approximate synchronization basin (MASB) and the shortest approximate synchronization time (SAST) are introduced and analyzed. Based on ASSS, several necessary and sufficient conditions are obtained for global and local approximate synchronization. MASB, the set of all possible initial states from which the systems are approximately synchronous, is investigated combining with the maximum invariant subset. Meanwhile, the calculation method of the SAST, associated with the transient period, is presented. By virtue of MASB and SAST, pinning controllers are designed to make the coupled systems achieve global approximate synchronization. Furthermore, the PSPACE-completeness of the approximate synchronization problem is proved. Finally, several examples are given to illustrate the obtained results. [ABSTRACT FROM AUTHOR]

In this paper, the mean-square exponential synchronization of stochastic multilayer networks with white-noise-based time-varying coupling is investigated via intermittent dynamic periodic event-triggered control. The existence of a dynamic term can reduce the number of event triggers. Furthermore, by introducing periodic sampling mechanism, a minimum inter-execution time is guaranteed to avoid Zeno phenomenon. Additionally, by employing Lyapunov method, graph theory, and stochastic analysis techniques, synchronization criteria for multilayer networks under intermittent dynamic periodic event-triggered control are established. To clarify the process of synchronization of multilayer networks, a brief framework is developed on the basis of Tajan's algorithm. Ultimately, theoretical results are applied into Chua's circuits and corresponding numerical simulations are given to illustrate the effectiveness and feasibility of the results. [ABSTRACT FROM AUTHOR]

This paper addresses the synchronization problem of fractional-order complex spatiotemporal networks (CSNs) based on partial differential equations with delays via boundary control. First, fractional-order CSNs with time-invariant and time-varying delays are studied separately due to the widespread existence of time delays in complex networks. Moreover, two boundary controllers are proposed to solve the synchronization issue of fractional-order CSNs, in which nodes communicate with each other only on the spatial boundary. Furthermore, according to the fractional-order inequality, the synchronization criteria of fractional-order CNSs with multiple delays are obtained. Finally, the numerical simulations are given to verify the feasibility of the presented results. A case provides the application of CSNs in image encryption. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of exponential synchronization and anti-synchronization for uncertain discrete-time neural networks (NNs) having time-varying delays with H ∞ performance in complex domain. An output-feedback controller is utilized not only to guarantee the synchronization criteria between the addressed discrete-time complex-valued neural networks (CVNNs) but also to reduce the effect of external disturbance. In order to assure the anti-synchronization criteria with H ∞ performance for the proposed CVNNs, we have introduced the output-feedback controller by anti-synchronization error analysis. With the help of Lyapunov–Krasovskii functional (LKF), some linear matrix inequality (LMI) based sufficient conditions are derived for both synchronization and anti-synchronization criteria which can be validated through YALMIP toolbox in MATLAB software. At last, a numerical simulation result is provided to verify the correctness of the established theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, we present a connectivity-preserving performance function approach for the distributed output-feedback synchronized tracking of uncertain heterogeneous nonlinear multiagent systems in a nonstrict-feedback form. Compared with existing output-feedback cooperative control results using neural networks, this paper contributes to developing a universal output-feedback synchronized control methodology that uses a connectivity-preserving performance function to ensure both initial network connectivity and preselected synchronization performance with a designable convergence time. To this end, a neural-network-based adaptive observer for each follower is designed to ensure the boundedness of estimation errors of unmeasurable states. Then, local event-triggered synchronized trackers using only relative output information and the connectivity-preserving performance function are constructed to guarantee the closed-loop stability in a low-complexity sense, where no adaptive neural networks and command filters are not required in the local trackers. Finally, a purely academic example and a practical platoon-control problem of multiple uncertain vehicular systems are considered to clarify and verify the proposed connectivity-preserving performance function approach in the simulation. [ABSTRACT FROM AUTHOR]

Copyright of Changement is the property of Solutions by HANDELSBLATT MEDIA GROUP GmbH and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

In this paper, an image algorithm using finite time synchronization is designed based on multi-scroll hyperchaotic system. A new ring-cutting scrambling is used in the algorithm to scramble the pictures in a relatively simple way. In the end, the encryption algorithm is completed by plane diffusion. In particular, the bit-plane algorithm needs to restore four bit-planes to get plaintext which can greatly reduce the deciphering ability. Experimental results show that the proposed algorithm can better resist violent attacks and cropping attacks through histogram, correlation coefficient red, and robustness tests. [ABSTRACT FROM AUTHOR]

This paper investigates the problem of master-slave synchronization of stochastic quaternion-valued neural networks (SQVNNs) with mixed time-varying delays. A linear feedback controller is developed to explore the global synchronization of the proposed system by utilizing the complete information of the time-delay state. Sufficient conditions for synchronization of the proposed model are derived by constructing appropriate Lyapunov–Krasovskii functional by applying the master-slave synchronization method of master-slave and some integral inequality techniques. Finally, a corresponding numerical simulation is presented to demonstrate the accuracy of the theoretical results. This paper introduces a unique and efficient image encryption algorithm based on SQVNNs. This technique utilizes the solution set of SQVNNs to generate the high-level randomness secret keys to encrypt the source image. Finally, we conclude that the algorithm yields a source image cipher with excellent diffusion and confusion properties. A few test clinical images are utilized to show the validity of the proposed method. Several performance analyses show that the proposed algorithm for image encryption gives an efficient and secure way to deal with the Internet of Health Things (IoHT). [ABSTRACT FROM AUTHOR]

In this article, without decomposing the quaternion-valued neural networks (QVNNs) into two complex-valued subsystems or four real-valued subsystems, quasi-projective synchronization of discrete-time fractional-order QVNNs is investigated. To this end, the sign function for quaternion number is introduced and some related properties are given. Then, two inequalities are built according to the nabla fractional difference and quaternion theory. Subsequently, a simple linear quaternion-valued controller is designed, and some synchronization conditions are given by means of our created inequalities. Finally, numerical simulations are given to prove the feasibility and correctness of the theoretical results. [ABSTRACT FROM AUTHOR]

The dissipative synchronization problem of delayed Markov jump switched neural networks (MJSNNs) under state-dependent switching by the event-triggered gain-scheduling control scheme is studied in this paper. By the introduction of a Markov jump model, which is used to depict the random variation wherein the connection of MJSNNs, the issues we study can take more generality. Via constructing suitable Lyapunov–Krasovskii functionals (LKFs) and applying some matrix inequality scaling methods, sufficient conditions for dissipative synchronization of delayed MJSNN are established. According to such criteria, the event-triggered gain-scheduling control scheme is adopted to design a controller with less terminal communication costs. Finally, a numerical example is given to demonstrate the effectiveness of the proposed method. [ABSTRACT FROM AUTHOR]

The cluster synchronization issues are investigated for directed coupled inertial reaction-diffusion neural networks (CIRDNNs) with nonidentical nodes by imposing two effective pinning control. A novel Lyapunov-Krasovskii functional (LKF) is established to directly analyze the dynamic behavior of CIRDNNs and deal with reaction-diffusion term, inertia term and coupling term. Moreover, based on different desired cluster synchronization states including a set of un-decoupled trajectories and the particular solutions of the decoupled node systems, two class of synchronization criteria in view of algebraic inequalities are derived under two different communication topologies, respectively. Finally, two typical examples are given to verify the theoretical results. [ABSTRACT FROM AUTHOR]

• The synchronization of hyperbolic coupled networks via aperiodically intermittent pinning control is firstly discussed. • The restriction τ ˙ < 1 on the time delay is removed. • Our models are more comprehensive and some existing results are special cases of ours. • A numerical example illustrates the validity of our findings. This paper is devoted to synchronization between two hyperbolic coupled networks (HCNs) with time-varying delays via aperiodically intermittent pinning control (AIPC). Based on the Lyapunov function with a piecewise continuous function, sufficient criteria of HCNs with internal delays only and with hybrid delays are obtained, separately. And it is found that the convergence speed of synchronization of HCNs with hybrid delays is slower than that with internal delays only. Furthermore, two simulation results are presented to verify the theoretical results. [ABSTRACT FROM AUTHOR]

In this paper, adaptive fixed-time synchronization(FTS) of stochastic memristor-based neural networks(MNNs) with discontinuous activations and mixed delays is investigated. Both continuous and discontinuous activation functions are discussed for stochastic MNNs. Meanwhile, a feedback control strategy and a new adaptive control strategy are proposed to ensure FTS of stochastic MNNs. Since the MNNs are right-hand discontinuous systems, the set-valued mapping and differential inclusion theory are used to deal with its discontinuity. Synchronization criteria and the settling time (ST) are obtained with the aid of some lemmas and mathematical inequalities under corresponding control schemes. It's worth noting that the ST can be adjusted to desired value by controller parameters regardless of the initial values. Finally, the feasibility of theoretical results are proved via simulation results. [ABSTRACT FROM AUTHOR]

This paper is dedicated to the global Mittag-Leffler synchronization (GMLS) of fractional-order inertial-type neural networks (FOITNNs) with time delays. To begin with, based on the semigroup property of the Caputo fractional derivative (CFD), an appropriate variable substitution is chosen to transform the original fractional-order inertial system into a traditional fractional-order system. Secondly, two types of discontinuous control schemes with delays and only a control input are proposed: one is the state feedback control and the other is the fractional-order adaptive control. On the basis of Lyapunov stability theory and fractional-order differential inequalities, some new sufficient criteria for the GMLS of two FOITNNs are established. Furthermore, the control gains here can be selected more widely, which makes the results more applicative and less conservative. Finally, two numerical examples validate the efficacy of the obtained results. [ABSTRACT FROM AUTHOR]

Copyright of Albéitar is the property of Grupo Asis Biomedia, S.L. and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

• The F-TS of FOQVBAMNNs with time-varying delays is explored in details. • A new lemma is established based on the Caputo fractional derivative. In addition, the fixed time is predicted, which is determined by the FO and the parameters involved in this new lemma. • The existence of the solution is proved by using the Banach contractive mapping principle. By virtue of several inequality techniques and a newly proved lemma, the criterion of achieving F-TS is derived, which is characterized as algebraic inequalities and convenient to be rationally verified. • The appropriate controllers are designed to realize the F-TS. In this paper, an estimate scheme for derivative order-dependent fixed-time synchronization (F-TS) on Caputo quaternion-valued BAM neural networks (QVBAMNNs) with time-varying delays is implemented. A novel fractional-order (FO) F-T stability lemma is established by the synthetic properties of fractional calculus. The appropriate feedback controllers are designed to realize the F-TS between the master-slave systems. Based on the Lyapunov functional method and multiple inequality techniques, the F-TS criterion of FOQVBAMNNs is obtained. Furthermore, the upper bound of settling time is predicted and controlled by the Caputo derivative order and system parameters, which is independent of the initial state. Finally, two simulation examples manifest the feasibility and validity of the results on F-TS and the control strategies. [ABSTRACT FROM AUTHOR]