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For: Xing X, Yao D, Lu Q, Li X. Finite-time stability of Markovian jump neural networks with partly unknown transition probabilities. Neurocomputing 2015;159:282-7. [DOI: 10.1016/j.neucom.2015.01.033] [Citation(s) in RCA: 21] [Impact Index Per Article: 2.3] [Reference Citation Analysis] [What about the content of this article? (0)] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
Number Cited by Other Article(s)
1
Sun S, Zhang H, Li W, Wang Y. Time-varying delay-dependent finite-time boundedness withHperformance for Markovian jump neural networks with state and input constraints. Neurocomputing 2021. [DOI: 10.1016/j.neucom.2020.10.088] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/23/2022]
2
Lin WJ, He Y, Zhang CK, Wu M. Stochastic Finite-Time H State Estimation for Discrete-Time Semi-Markovian Jump Neural Networks With Time-Varying Delays. IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS 2020;31:5456-5467. [PMID: 32071007 DOI: 10.1109/tnnls.2020.2968074] [Citation(s) in RCA: 19] [Impact Index Per Article: 4.8] [Reference Citation Analysis] [Abstract] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Indexed: 06/10/2023]
3
Stability of Impulsive Stochastic Reaction Diffusion Recurrent Neural Network. Neural Process Lett 2019. [DOI: 10.1007/s11063-019-10131-8] [Citation(s) in RCA: 4] [Impact Index Per Article: 0.8] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 10/25/2022]
4
Sakthivel R, Parivallal A, Kaviarasan B, Lee H, Lim Y. Finite-time consensus of Markov jumping multi-agent systems with time-varying actuator faults and input saturation. ISA TRANSACTIONS 2018;83:89-99. [PMID: 30241915 DOI: 10.1016/j.isatra.2018.08.016] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.2] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/13/2017] [Revised: 08/14/2018] [Accepted: 08/31/2018] [Indexed: 06/08/2023]
5
Dissipativity-based asynchronous state estimation for Markov jump neural networks with jumping fading channels. Neurocomputing 2017. [DOI: 10.1016/j.neucom.2017.02.032] [Citation(s) in RCA: 7] [Impact Index Per Article: 1.0] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/19/2022]
6
Zheng CD, Xian Y, Wang Z. Third-order reciprocally convex approach to stability of fuzzy cellular neural networks under impulsive perturbations. Soft comput 2017. [DOI: 10.1007/s00500-016-2051-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.1] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
7
Zhao H, Li L, Peng H, Xiao J, Yang Y, Zheng M. Finite-time topology identification and stochastic synchronization of complex network with multiple time delays. Neurocomputing 2017. [DOI: 10.1016/j.neucom.2016.09.014] [Citation(s) in RCA: 23] [Impact Index Per Article: 3.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
8
Finite-time stochastic boundedness of discrete-time Markovian jump neural networks with boundary transition probabilities and randomly varying nonlinearities. Neurocomputing 2016. [DOI: 10.1016/j.neucom.2015.09.101] [Citation(s) in RCA: 10] [Impact Index Per Article: 1.3] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/21/2022]
9
Hien L, Dzung N, Trinh H. Stochastic stability of nonlinear discrete-time Markovian jump systems with time-varying delay and partially unknown transition rates. Neurocomputing 2016. [DOI: 10.1016/j.neucom.2015.10.081] [Citation(s) in RCA: 13] [Impact Index Per Article: 1.6] [Reference Citation Analysis] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/30/2022]
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