Predefined-time synchronization of incommensurate fractional-order competitive neural networks with time-varying delays

Zhao, 2022, Distributed event-triggered impulsive tracking control for fractional-order multiagent networks, IEEE Trans Syst Man Cybern Syst, 52, 4544, 10.1109/TSMC.2021.3096975 Banchuin, 2023, On the noise performances of fractal-fractional electrical circuits, Int J Cir Theor Appl, 51, 80, 10.1002/cta.3407 Hao, 2023, Passive realization of the fractional-order capacitor based on fractional-order inductor and its application, Int J Cir Theor Appl, 51, 2607, 10.1002/cta.3554 Ogri, 2021, Novel fractional-order Jacobi moments and invariant moments for pattern recognition applications, Neural Comput Appl, 33, 13539, 10.1007/s00521-021-05977-w Kilbas, 2006 Gu, 2019, Synchronization for incommensurate Riemann–Liouville fractional-order time-delayed competitive neural networks with different time scales and known or unknown parameters, J Comput Nonlinear Dyn, 14 Peng, 2023, Asymptotic synchronization of second-fractional-order fuzzy neural networks with impulsive effects, Chaos Solitons Fractals, 168, 10.1016/j.chaos.2023.113150 Peng, 2023, Synchronization analysis of fractional-order inertial-type neural networks with time delays, Math Comput Simulation, 205, 62, 10.1016/j.matcom.2022.09.023 Cohen, 1983, Absolute stability of global pattern formation and parallel memory storage by competitive neural networks, IEEE Trans Syst Man Cybern, 13, 815, 10.1109/TSMC.1983.6313075 Meyer-Bäse, 1996, Singular perturbation analysis of competitive neural networks with different time-scales, Neural Comput, 8, 1731, 10.1162/neco.1996.8.8.1731 Lu, 2005, Global exponential stability of delayed competitive neural networks with different time scales, Neural Netw, 18, 243, 10.1016/j.neunet.2004.11.009 Shi, 2014, Synchronization of memristive competitive neural networks with different time scales, Neural Comput Appl, 25, 1163, 10.1007/s00521-014-1598-9 Zhao, 2021, Synchronization of coupled memristive competitive BAM neural networks with different time scales, Neurocomputing, 427, 110, 10.1016/j.neucom.2020.11.023 Yang, 2022, Fixed-time synchronization of competitive neural networks with multiple time scales, IEEE Trans Neural Netw Learn Syst, 33, 4133, 10.1109/TNNLS.2021.3052868 Wu, 2023, Coexistence and local stability of multiple equilibrium points for fractional-order state-dependent switched competitive neural networks with time-varying delays, Neural Netw, 160, 132, 10.1016/j.neunet.2022.12.013 Zhang, 2021, Multistability of delayed fractional-order competitive neural networks, Neural Netw, 140, 325, 10.1016/j.neunet.2021.03.036 Pratap, 2019, Stability and synchronization criteria for fractional order competitive neural networks with time delays: An asymptotic expansion of Mittag Leffler function, J Franklin Inst, 356, 2212, 10.1016/j.jfranklin.2019.01.017 Pratap, 2019, Stability analysis and robust synchronization of fractional-order competitive neural networks with different time scales and impulsive perturbations, Internat J Adapt Control Signal Process, 33, 1635, 10.1002/acs.3056 Xu, 2021, Global asymptotic stability of fractional-order competitive neural networks with multiple time-varying-delay links, Appl Math Comput, 389, 10.1016/j.amc.2020.125498 Yang, 2021, Synchronization for fractional-order reaction–diffusion competitive neural networks with leakage and discrete delays, Neurocomputing, 436, 47, 10.1016/j.neucom.2021.01.009 Wang, 2023, Predefined-time synchronization of fractional-order memristive competitive neural networks with time-varying delays, Chaos Solitons Fractals, 174, 10.1016/j.chaos.2023.113790 Rajchakit, 2020, Impulsive effects on stability and passivity analysis of memristor-based fractional-order competitive neural networks, Neurocomputing, 417, 290, 10.1016/j.neucom.2020.07.036 Jia, 2021, Global stabilization of fractional-order memristor-based neural networks with incommensurate orders and multiple time-varying delays: a positive-system-based approach, Nonlinear Dynam, 104, 2303, 10.1007/s11071-021-06403-5 Jia, 2022, Lag quasi-synchronization of incommensurate fractional-order memristor-based neural networks with nonidentical characteristics via quantized control: A vector fractional halanay inequality approach, J Franklin Inst, 359, 6392, 10.1016/j.jfranklin.2022.05.017 Jia, 2022, Bipartite leader-following synchronization of delayed incommensurate fractional-order memristor-based neural networks under signed digraph via adaptive strategy, Neurocomputing, 505, 413, 10.1016/j.neucom.2022.06.043 Yang, 2021, Exponential synchronization of fractional-order reaction–diffusion coupled neural networks with hybrid delay-dependent impulses, J Franklin Inst, 358, 3167, 10.1016/j.jfranklin.2021.02.003 Zheng, 2022, Mittag-Leffler synchronization of fractional-order coupled neural networks with mixed delays, Appl Math Comput, 430, 10.1016/j.amc.2022.127303 Zhao, 2023, Quasi-projective synchronization of discrete-time fractional-order quaternion-valued neural networks, J Franklin Inst, 360, 3263, 10.1016/j.jfranklin.2023.01.024 Liu, 2020, Pinning synchronization of coupled fractional-time-varying delayed neural networks with arbitrary fixed topology, Neurocomputing, 400, 46, 10.1016/j.neucom.2020.03.029 Zhang, 2022, Quantized intermittent control tactics for exponential synchronization of quaternion-valued memristive delayed neural networks, ISA Trans, 126, 288, 10.1016/j.isatra.2021.07.029 Zhang, 2021, New results on synchronization for second-order fuzzy memristive neural networks with time-varying and infinite distributed delays, Knowl-Based Syst, 230, 10.1016/j.knosys.2021.107397 Hui, 2023, Finite-time synchronization of fractional-order memristive neural networks via feedback and periodically intermittent control, Commun Nonlinear Sci Numer Simul, 116, 10.1016/j.cnsns.2022.106822 Zhao, 2022, Finite-time synchronization of fractional-order fuzzy cohen-grossberg neural networks with time delay, Iran J Fuzzy Syst, 19, 47 Zhao, 2023, Finite-time synchronization of fractional-order delayed memristive fuzzy neural networks, Fuzzy Sets and Systems, 467, 10.1016/j.fss.2023.108578 Polyakov, 2012, Nonlinear feedback design for fixed-time stabilization of linear control systems, IEEE Trans Automat Control, 57, 2106, 10.1109/TAC.2011.2179869 Hu, 2017, Fixed-time stability of dynamical systems and fixed-time synchronization of coupled discontinuous neural networks, Neural Netw, 89, 74, 10.1016/j.neunet.2017.02.001 Chen, 2019, A new fixed-time stability theorem and its application to the synchronization control of memristive neural networks, Neurocomputing, 349, 290, 10.1016/j.neucom.2019.03.040 Chen, 2020, A new fixed-time stability theorem and its application to the fixed-time synchronization of neural networks, Neural Netw, 123, 412, 10.1016/j.neunet.2019.12.028 Tang, 2023, New fixed-time stability criterion and fixed-time synchronization of neural networks via non-chattering control, Neural Comput Appl, 35, 6029, 10.1007/s00521-022-07975-y Zhang, 2020, A new fixed-time stability criterion and its application to synchronization control of memristor-based fuzzy inertial neural networks with proportional delay, Neural Process Lett, 52, 1291, 10.1007/s11063-020-10305-9 Hu, 2021, Fixed/preassigned-time synchronization of complex networks via improving fixed-time stability, IEEE Trans Cybern, 51, 2882, 10.1109/TCYB.2020.2977934 Kong, 2022, Improved fixed-time stability lemma of discontinuous system and its application, IEEE Trans Cir Syst I: Reg Pap, 69, 835 Kong, 2023, Fixed-time stabilization of leakage-delayed neural networks modeled by delayed Filippov systems: leakage-delay-dependent settling-time, IEEE Trans Netw Sci Eng, 10, 2154, 10.1109/TNSE.2023.3243130 Kong, 2023, Fixed-time stabilization of discontinuous neutral neural networks with proportional delays via new fixed-time stability lemmas, IEEE Trans Neural Netw Learn Syst, 34, 775, 10.1109/TNNLS.2021.3101252 Sánchez-Torres J, Sanchez E, Loukianov A. Predefined-time stability of dynamical systems with sliding modes. In: IEEE American control conference. 2015, p. 5842–6. Wang, 2022, Predefined-time synchronization of stochastic memristor-based bidirectional associative memory neural networks with time-varying delays, IEEE Trans Cogn Develop Syst, 14, 1584, 10.1109/TCDS.2021.3126759 Lin, 2023, Predefined-time stability control method based on Lyapunov function, J Huazhong Univ Sci Tech(Natural Sci Edi), 51, 47 Lin, 2020, Enhancing the settling time estimation of fixed-time stability and applying it to the predefined-time synchronization of delayed memristive neural networks with external unknown disturbance, Chaos, 30, 10.1063/5.0010145 Pu, 2023, Fixed/predefined-time synchronization of complex-valued discontinuous delayed neural networks via non-chattering and saturation control, Physica A, 610, 10.1016/j.physa.2022.128425 Lin, 2021, Adaptive predefined-time synchronization of two different fractional-order chaotic systems with time-delay, IEEE Access, 9, 31908, 10.1109/ACCESS.2021.3059324 Lin, 2020, Predefined-time antisynchronization of two different chaotic neural networks, Complexity, 2020, 10.1155/2020/7476250 Liu, 2022, A new predefined-time stability theorem and its application in the synchronization of memristive complex-valued BAM neural networks, Neural Netw, 153, 152, 10.1016/j.neunet.2022.05.031 Gan, 2022, Improved results on fixed-/preassigned-time synchronization for memristive complex-valued neural networks, IEEE Trans Neural Netw Learn Syst, 33, 5542, 10.1109/TNNLS.2021.3070966 Zhang, 2023, New results on fixed/predefined-time synchronization of delayed fuzzy inertial discontinuous neural networks: non-reduced order approach, Appl Math Comput, 440, 10.1016/j.amc.2022.127671 Khalil, 2002 Lin, 2017, Synchronization of uncertain fractional-order chaotic systems with time delay based on adaptive neural network control, Acta Phys Sin, 66 Chen, 2015, Global asymptotical ω-periodicity of a fractional-order nonautonomous neural networks, Neural Netw, 68, 78, 10.1016/j.neunet.2015.04.006