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Sader M, Li W, Jiang H, Chen Z, Liu Z. Semi-Global Bipartite Fault-Tolerant Containment Control for Heterogeneous Multiagent Systems With Antagonistic Communication Networks and Input Saturation. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2024; 35:6265-6272. [PMID: 36173780 DOI: 10.1109/tnnls.2022.3208449] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/16/2023]
Abstract
Semi-global bipartite fault-tolerant containment control framework on antagonistic communication networks is proposed in this article for heterogeneous multiagent systems (MASs) under the influence of input saturation and actuator faults. An observer is constructed to estimate the leaders' states on signed digraph, where the communication networks are antagonistic. A fully distributed virtual control approach is developed to acquire the containment trajectory. Based on the observer, a semi-global containment control method is developed to compensate for the detrimental impacts of both input saturation and actuator faults. Besides, the dynamics and state-space dimensions of the agents can be different. The proposed framework overcomes two drawbacks of the conventional containment control: 1) the containment trajectory is obtained under general antagonistic communication networks, which is more general in engineering applications and 2) both actuator faults and input saturation are solved for heterogeneous agents, which relaxes the limitation of homogeneous dynamics. Finally, a simulation example is conducted to test and verify the feasibility of the proposed method framework.
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Shen H, Huang Z, Wu Z, Cao J, Park JH. Nonfragile H ∞ Synchronization of BAM Inertial Neural Networks Subject to Persistent Dwell-Time Switching Regularity. IEEE TRANSACTIONS ON CYBERNETICS 2022; 52:6591-6602. [PMID: 34705662 DOI: 10.1109/tcyb.2021.3119199] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/13/2023]
Abstract
This article concentrates on the synchronization of discrete-time persistent dwell-time (PDT) switched bidirectional associative memory inertial neural networks with time-varying delays. Through the use of the switched system theory related to the PDT, the convex optimization technique together with some straightforward decoupling methods, an appropriate mode-dependent controller with nonfragility is developed to acclimatize itself to some practical circumstances. Simultaneously, sufficient conditions of ensuring the H∞ performance and exponential stability for the resulting switched synchronization error system are derived. Finally, a numerical example is utilized to show the validity of the model constructed and the influence of the PDT on the H∞ performance. In addition, an image encryption example is employed to show the potential application prospect of the investigated system.
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Observer-based distributed consensus for multi-agent systems with directed networks and input saturation. Neurocomputing 2021. [DOI: 10.1016/j.neucom.2020.09.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/20/2022]
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4
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Tanskanen JM, Ahtiainen A, Hyttinen JA. Toward Closed-Loop Electrical Stimulation of Neuronal Systems: A Review. Bioelectricity 2020; 2:328-347. [PMID: 34471853 PMCID: PMC8370352 DOI: 10.1089/bioe.2020.0028] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 01/24/2023] Open
Abstract
Biological neuronal cells communicate using neurochemistry and electrical signals. The same phenomena also allow us to probe and manipulate neuronal systems and communicate with them. Neuronal system malfunctions cause a multitude of symptoms and functional deficiencies that can be assessed and sometimes alleviated by electrical stimulation. Our working hypothesis is that real-time closed-loop full-duplex measurement and stimulation paradigms can provide more in-depth insight into neuronal networks and enhance our capability to control diseases of the nervous system. In this study, we review extracellular electrical stimulation methods used in in vivo, in vitro, and in silico neuroscience research and in the clinic (excluding methods mainly aimed at neuronal growth and other similar effects) and highlight the potential of closed-loop measurement and stimulation systems. A multitude of electrical stimulation and measurement-based methods are widely used in research and the clinic. Closed-loop methods have been proposed, and some are used in the clinic. However, closed-loop systems utilizing more complex measurement analysis and adaptive stimulation systems, such as artificial intelligence systems connected to biological neuronal systems, do not yet exist. Our review promotes the research and development of intelligent paradigms aimed at meaningful communications between neuronal and information and communications technology systems, "dialogical paradigms," which have the potential to take neuroscience and clinical methods to a new level.
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Affiliation(s)
- Jarno M.A. Tanskanen
- BioMediTech Institute and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Annika Ahtiainen
- BioMediTech Institute and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
| | - Jari A.K. Hyttinen
- BioMediTech Institute and Faculty of Medicine and Health Technology, Tampere University, Tampere, Finland
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Zhao J, Xu S, Li Y, Chu Y, Zhang Z. Event-triggering H∞ synchronization for discrete time switched complex networks via the quasi-time asynchronous controller. Neurocomputing 2020. [DOI: 10.1016/j.neucom.2020.05.003] [Citation(s) in RCA: 5] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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6
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Mu G, Li L, Li X. Quasi-bipartite synchronization of signed delayed neural networks under impulsive effects. Neural Netw 2020; 129:31-42. [DOI: 10.1016/j.neunet.2020.05.012] [Citation(s) in RCA: 8] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/04/2020] [Revised: 04/19/2020] [Accepted: 05/11/2020] [Indexed: 10/24/2022]
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She B, Mehta S, Ton C, Kan Z. Controllability Ensured Leader Group Selection on Signed Multiagent Networks. IEEE TRANSACTIONS ON CYBERNETICS 2020; 50:222-232. [PMID: 30235162 DOI: 10.1109/tcyb.2018.2868470] [Citation(s) in RCA: 3] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
Leader-follower controllability on signed multiagent networks is investigated in this paper. Specifically, we consider a dynamic signed multiagent network, where the agents interact via neighbor-based Laplacian feedback and the network allows positive and negative edges to capture cooperative and competitive interactions among agents. The agents are classified as either leaders or followers, thus forming a leader-follower signed network. To enable full control of the leader-follower signed network, controllability ensured leader group selection approaches are investigated in this paper, that is, identifying a small subset of nodes in the signed network, such that the selected nodes are able to drive the network to a desired behavior, even in the presence of antagonistic interactions. In particular, graphical characterizations of the controllability of signed networks are first developed based on the investigation of the interaction between network topology and agent dynamics. Since signed path and cycle graphs are basic building blocks for a variety of networks, the developed topological characterizations are then exploited to develop leader selection methods for signed path and cycle graphs to ensure leader-follower controllability. Along with illustrative examples, heuristic algorithms are also developed showing how leader selection methods developed for path and cycle graphs can be potentially extended to more general signed networks. In contrast to existing results that mainly focus on unsigned networks, this paper characterizes controllability and develops leader selection methods for signed networks. In addition, the developed results are generic, in the sense that they are not only applicable to signed networks but also to unsigned networks, since unsigned networks are a particular case of signed networks that only contain positive edges.
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Synchronization of impulsive coupled complex-valued neural networks with delay: The matrix measure method. Neural Netw 2019; 117:285-294. [DOI: 10.1016/j.neunet.2019.05.024] [Citation(s) in RCA: 38] [Impact Index Per Article: 7.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/23/2018] [Revised: 05/09/2019] [Accepted: 05/24/2019] [Indexed: 11/21/2022]
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Liu Y, Zhang D, Lou J, Lu J, Cao J. Stability Analysis of Quaternion-Valued Neural Networks: Decomposition and Direct Approaches. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2018; 29:4201-4211. [PMID: 29989971 DOI: 10.1109/tnnls.2017.2755697] [Citation(s) in RCA: 49] [Impact Index Per Article: 8.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/08/2023]
Abstract
In this paper, we investigate the global stability of quaternion-valued neural networks (QVNNs) with time-varying delays. On one hand, in order to avoid the noncommutativity of quaternion multiplication, the QVNN is decomposed into four real-valued systems based on Hamilton rules: $ij=-ji=k,~jk=-kj=i$ , $ki=-ik=j$ , $i^{2}=j^{2}=k^{2}=ijk=-1$ . With the Lyapunov function method, some criteria are, respectively, presented to ensure the global $\mu $ -stability and power stability of the delayed QVNN. On the other hand, by considering the noncommutativity of quaternion multiplication and time-varying delays, the QVNN is investigated directly by the techniques of the Lyapunov-Krasovskii functional and the linear matrix inequality (LMI) where quaternion self-conjugate matrices and quaternion positive definite matrices are used. Some new sufficient conditions in the form of quaternion-valued LMI are, respectively, established for the global $\mu $ -stability and exponential stability of the considered QVNN. Besides, some assumptions are presented for the two different methods, which can help to choose quaternion-valued activation functions. Finally, two numerical examples are given to show the feasibility and the effectiveness of the main results.
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Li F, Yan H, Karimi HR. Single-Input Pinning Controller Design for Reachability of Boolean Networks. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2018; 29:3264-3269. [PMID: 28613183 DOI: 10.1109/tnnls.2017.2705109] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.2] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
This brief is concerned with the problem of a single-input pinning control design for reachability of Boolean networks (BNs). Specifically, the transition matrix of a BN is designed to steer the BN from an initial state to a desirable one. In addition, some nodes are selected as the pinning nodes by solving some logical matrix equations. Furthermore, a single-input pinning control algorithm is given. Eventually, a genetic regulatory network is provided to demonstrate the effectiveness and feasibility of the developed method.
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Zhang D, Wang QG, Srinivasan D, Li H, Yu L. Asynchronous State Estimation for Discrete-Time Switched Complex Networks With Communication Constraints. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2018; 29:1732-1746. [PMID: 28368834 DOI: 10.1109/tnnls.2017.2678681] [Citation(s) in RCA: 33] [Impact Index Per Article: 5.5] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/07/2023]
Abstract
This paper is concerned with the asynchronous state estimation for a class of discrete-time switched complex networks with communication constraints. An asynchronous estimator is designed to overcome the difficulty that each node cannot access to the topology/coupling information. Also, the event-based communication, signal quantization, and the random packet dropout problems are studied due to the limited communication resource. With the help of switched system theory and by resorting to some stochastic system analysis method, a sufficient condition is proposed to guarantee the exponential stability of estimation error system in the mean-square sense and a prescribed performance level is also ensured. The characterization of the desired estimator gains is derived in terms of the solution to a convex optimization problem. Finally, the effectiveness of the proposed design approach is demonstrated by a simulation example.
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Zhang W, Tang Y, Huang T, Kurths J. Sampled-Data Consensus of Linear Multi-agent Systems With Packet Losses. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2017; 28:2516-2527. [PMID: 27542186 DOI: 10.1109/tnnls.2016.2598243] [Citation(s) in RCA: 12] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.In this paper, the consensus problem is studied for a class of multi-agent systems with sampled data and packet losses, where random and deterministic packet losses are considered, respectively. For random packet losses, a Bernoulli-distributed white sequence is used to describe packet dropouts among agents in a stochastic way. For deterministic packet losses, a switched system with stable and unstable subsystems is employed to model packet dropouts in a deterministic way. The purpose of this paper is to derive consensus criteria, such that linear multi-agent systems with sampled-data and packet losses can reach consensus. By means of the Lyapunov function approach and the decomposition method, the design problem of a distributed controller is solved in terms of convex optimization. The interplay among the allowable bound of the sampling interval, the probability of random packet losses, and the rate of deterministic packet losses are explicitly derived to characterize consensus conditions. The obtained criteria are closely related to the maximum eigenvalue of the Laplacian matrix versus the second minimum eigenvalue of the Laplacian matrix, which reveals the intrinsic effect of communication topologies on consensus performance. Finally, simulations are given to show the effectiveness of the proposed results.
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Affiliation(s)
- Wenbing Zhang
- Department of Mathematics, Yangzhou University, Yangzhou, China
| | - Yang Tang
- Key Laboratory of Advanced Control and Optimization for Chemical Processes, Ministry of Education, East China University of Science and Technology, Shanghai, China
| | | | - Jurgen Kurths
- Potsdam Institute for Climate Impact Research, Potsdam, Germany
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Decomposition approach to the stability of recurrent neural networks with asynchronous time delays in quaternion field. Neural Netw 2017; 94:55-66. [DOI: 10.1016/j.neunet.2017.06.014] [Citation(s) in RCA: 42] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/08/2017] [Revised: 05/26/2017] [Accepted: 06/26/2017] [Indexed: 11/23/2022]
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15
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Ho DWC. A Layered Event-Triggered Consensus Scheme. IEEE TRANSACTIONS ON CYBERNETICS 2017; 47:2334-2340. [PMID: 27295698 DOI: 10.1109/tcyb.2016.2571122] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/06/2023]
Abstract
This paper studies the dynamics of multiagent systems with a multilayer structure, proposing a novel layered event-triggered scheme (LETS) for consensus. This LETS emphasizes on synchronous information transmission in the same layer but asynchronous message update between different layers, which differs from the existing centralized or distributed event-triggered schemes. Moreover, under the LETS, agents in different layers achieve asymptotical consensus eventually and the Zeno behavior is successfully eliminated. Furthermore, an algorithm is provided to avoid continuous event detection, verified by a numerical example.
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Xu W, Ho DWC, Li L, Cao J. Event-Triggered Schemes on Leader-Following Consensus of General Linear Multiagent Systems Under Different Topologies. IEEE TRANSACTIONS ON CYBERNETICS 2017; 47:212-223. [PMID: 26731787 DOI: 10.1109/tcyb.2015.2510746] [Citation(s) in RCA: 82] [Impact Index Per Article: 11.7] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
This paper investigates the leader-following consensus for multiagent systems with general linear dynamics by means of event-triggered scheme (ETS). We propose three types of schemes, namely, distributed ETS (distributed-ETS), centralized ETS (centralized-ETS), and clustered ETS (clustered-ETS) for different network topologies. All these schemes guarantee that all followers can track the leader eventually. It should be emphasized that all event-triggered protocols in this paper depend on local information and their executions are distributed. Moreover, it is shown that such event-triggered mechanism can significantly reduce the frequency of control's update. Further, positive inner-event time intervals are assured for those cases of distributed-ETS, centralized-ETS, and clustered-ETS. In addition, two methods are proposed to avoid continuous communication between agents for event detection. Finally, numerical examples are provided to illustrate the effectiveness of the ETSs.
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Tang Y, Gao H, Kurths J. Robust $H_{\infty }$ Self-Triggered Control of Networked Systems Under Packet Dropouts. IEEE TRANSACTIONS ON CYBERNETICS 2016; 46:3294-3305. [PMID: 26672057 DOI: 10.1109/tcyb.2015.2502619] [Citation(s) in RCA: 6] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
This paper is concerned with robust H∞ self-triggered control of networked systems. The system considered here includes parameter uncertainties, packet dropouts, and time delays. The time delay is described in a stochastic way, which takes a value from a given finite set. In order to compensate for the existence of deterministic packet dropouts, a new self-triggered control scheme is proposed. The main feature of the proposed self-triggered control strategy is that the next control task is predicted based on the self-triggered technique, in which the predicted event interval is divided equally for the sake of packet dropouts. The triggered condition is developed to ensure the stability of the uncertain sampled system by utilizing an uncertain algebraic Riccati equation and the comparison principle. Finally, an example of the inverted pendulum of a cart is provided to illustrate the effectiveness of the proposed results.
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18
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New results on anti-synchronization of switched neural networks with time-varying delays and lag signals. Neural Netw 2016; 81:52-8. [DOI: 10.1016/j.neunet.2016.05.004] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/21/2015] [Revised: 01/28/2016] [Accepted: 05/09/2016] [Indexed: 11/23/2022]
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Liu Y, Zhang D, Lu J, Cao J. Global μ-stability criteria for quaternion-valued neural networks with unbounded time-varying delays. Inf Sci (N Y) 2016. [DOI: 10.1016/j.ins.2016.04.033] [Citation(s) in RCA: 105] [Impact Index Per Article: 13.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/21/2022]
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Wu X, Tang Y, Cao J, Zhang W. Distributed Consensus of Stochastic Delayed Multi-agent Systems Under Asynchronous Switching. IEEE TRANSACTIONS ON CYBERNETICS 2016; 46:1817-1827. [PMID: 26292354 DOI: 10.1109/tcyb.2015.2453346] [Citation(s) in RCA: 8] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/04/2023]
Abstract
In this paper, the distributed exponential consensus of stochastic delayed multi-agent systems with nonlinear dynamics is investigated under asynchronous switching. The asynchronous switching considered here is to account for the time of identifying the active modes of multi-agent systems. After receipt of confirmation of mode's switching, the matched controller can be applied, which means that the switching time of the matched controller in each node usually lags behind that of system switching. In order to handle the coexistence of switched signals and stochastic disturbances, a comparison principle of stochastic switched delayed systems is first proved. By means of this extended comparison principle, several easy to verified conditions for the existence of an asynchronously switched distributed controller are derived such that stochastic delayed multi-agent systems with asynchronous switching and nonlinear dynamics can achieve global exponential consensus. Two examples are given to illustrate the effectiveness of the proposed method.
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A Novel Method to Magnetic Flux Linkage Optimization of Direct-Driven Surface-Mounted Permanent Magnet Synchronous Generator Based on Nonlinear Dynamic Analysis. ENERGIES 2016. [DOI: 10.3390/en9070557] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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22
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Tang Y, Gao H, Du W, Lu J, Vasilakos AV, Kurths J. Robust Multiobjective Controllability of Complex Neuronal Networks. IEEE/ACM TRANSACTIONS ON COMPUTATIONAL BIOLOGY AND BIOINFORMATICS 2016; 13:778-791. [PMID: 26441452 DOI: 10.1109/tcbb.2015.2485226] [Citation(s) in RCA: 2] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/05/2023]
Abstract
This paper addresses robust multiobjective identification of driver nodes in the neuronal network of a cat's brain, in which uncertainties in determination of driver nodes and control gains are considered. A framework for robust multiobjective controllability is proposed by introducing interval uncertainties and optimization algorithms. By appropriate definitions of robust multiobjective controllability, a robust nondominated sorting adaptive differential evolution (NSJaDE) is presented by means of the nondominated sorting mechanism and the adaptive differential evolution (JaDE). The simulation experimental results illustrate the satisfactory performance of NSJaDE for robust multiobjective controllability, in comparison with six statistical methods and two multiobjective evolutionary algorithms (MOEAs): nondominated sorting genetic algorithms II (NSGA-II) and nondominated sorting composite differential evolution. It is revealed that the existence of uncertainties in choosing driver nodes and designing control gains heavily affects the controllability of neuronal networks. We also unveil that driver nodes play a more drastic role than control gains in robust controllability. The developed NSJaDE and obtained results will shed light on the understanding of robustness in controlling realistic complex networks such as transportation networks, power grid networks, biological networks, etc.
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Li L, Ho DW, Cao J, Lu J. Pinning cluster synchronization in an array of coupled neural networks under event-based mechanism. Neural Netw 2016; 76:1-12. [DOI: 10.1016/j.neunet.2015.12.008] [Citation(s) in RCA: 70] [Impact Index Per Article: 8.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2015] [Revised: 11/29/2015] [Accepted: 12/11/2015] [Indexed: 10/22/2022]
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The Universal Approximation Capabilities of Cylindrical Approximate Identity Neural Networks. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2016. [DOI: 10.1007/s13369-016-2067-9] [Citation(s) in RCA: 5] [Impact Index Per Article: 0.6] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 11/24/2022]
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25
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Tong L, Wong W, Kwong C. Differential evolution-based optimal Gabor filter model for fabric inspection. Neurocomputing 2016. [DOI: 10.1016/j.neucom.2015.09.011] [Citation(s) in RCA: 74] [Impact Index Per Article: 9.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/25/2022]
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26
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Community Detection Utilizing a Novel Multi-swarm Fruit Fly Optimization Algorithm with Hill-Climbing Strategy. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2015. [DOI: 10.1007/s13369-015-1905-5] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/22/2022]
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27
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Synchronization of Coupled Switched Neural Networks with Time-Varying Delays. ARABIAN JOURNAL FOR SCIENCE AND ENGINEERING 2015. [DOI: 10.1007/s13369-015-1812-9] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
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28
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Pan Y, Zhou Q, Lu Q, Wu C. New dissipativity condition of stochastic fuzzy neural networks with discrete and distributed time-varying delays. Neurocomputing 2015. [DOI: 10.1016/j.neucom.2015.03.045] [Citation(s) in RCA: 15] [Impact Index Per Article: 1.7] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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29
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Finite-time stability of Markovian jump neural networks with partly unknown transition probabilities. Neurocomputing 2015. [DOI: 10.1016/j.neucom.2015.01.033] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
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30
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Robust finite-time state estimation of uncertain neural networks with Markovian jump parameters. Neurocomputing 2015. [DOI: 10.1016/j.neucom.2015.01.052] [Citation(s) in RCA: 19] [Impact Index Per Article: 2.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/18/2022]
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31
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Xu Z, Su H, Xu H, Wu ZG. Asynchronous H∞ filtering for discrete-time Markov jump neural networks. Neurocomputing 2015. [DOI: 10.1016/j.neucom.2015.01.040] [Citation(s) in RCA: 18] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/17/2022]
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32
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Xing X, Pan Y, Lu Q, Cui H. New mean square exponential stability condition of stochastic fuzzy neural networks. Neurocomputing 2015. [DOI: 10.1016/j.neucom.2014.12.076] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/24/2022]
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