Reliable stability and stabilizability for complex-valued memristive neural networks with actuator failures and aperiodic event-triggered sampled-data control
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Publication:2061230
DOI10.1016/j.nahs.2020.100977OpenAlexW3090947085MaRDI QIDQ2061230
Ruimei Zhang, Jun Cheng, Guo-Cheng Wu, Shou-ming Zhong, Juhyun Park, De-Qiang Zeng
Publication date: 13 December 2021
Published in: Nonlinear Analysis. Hybrid Systems (Search for Journal in Brave)
Full work available at URL: https://doi.org/10.1016/j.nahs.2020.100977
stabilitystabilizabilityactuator failuresreliable controlaperiodic event-triggered sampled-data controlcomplex-valued memristive neural networks (CVMNNs)
Related Items (8)
Experimental validation of disturbance observer-based adaptive terminal sliding mode control subject to control input limitations for SISO and MIMO systems ⋮ Pinning multisynchronization of delayed fractional-order memristor-based neural networks with nonlinear coupling and almost-periodic perturbations ⋮ Adaptive event-triggered control for networked interconnected systems with cyber-attacks ⋮ Observer-based sliding mode synchronization control of complex-valued neural networks with inertial term and mixed time-varying delays ⋮ Memory-based event-triggered asynchronous control for semi-Markov switching systems ⋮ Mittag-Leffler stability and synchronization for FOQVFNNs including proportional delay and Caputo derivative via fractional differential inequality approach ⋮ Point-sampled-data passivity stabilization of stochastic complex-valued memristor networks with multi-delays and reaction-diffusion term: a switching model approach ⋮ Fuzzy filter design for affine systems with sensor faults: a dynamic event-triggered approach
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