W Qian, Y Li, Y Zhao, Y Chen - Neurocomputing, 2020 - Elsevier
This proposal considers the issue of L 2-L∞ state estimation for delayed neural networks. A novel Lyapunov-Krasovskii functional is constructed, which contains augmented s …
W Xie, R Zhang, D Zeng, K Shi… - International Journal of …, 2020 - Wiley Online Library
This paper investigates the strictly dissipative stabilization problem for multiple‐memory Markov jump systems with network communication protocol. Firstly, for reducing data …
This paper investigates the synchronization and stability problem of fractional-order memristive quaternion-valued neural networks (FMQVNNs) with time delay and uncertain …
W Xie, H Zhu, J Cheng, S Zhong, K Shi - Information Sciences, 2019 - Elsevier
This paper investigates the problem of asynchronous H∞ resilient filter design for delayed switched neural networks with memory unideal measurements over a finite-time interval. We …
This paper addresses the dissipativity analysis and controller design for a class of TS fuzzy positive systems which are described by the Roesser model. First, sufficient conditions …
T Wu, J Cao, L Xiong, X Xie - International Journal of Robust …, 2020 - Wiley Online Library
This article deals with the problems of exponential stability and extended dissipative analysis for a class of uncertain memristive neural networks (MNNs) with additive time …
W Xie, H Zhu, S Zhong, J Cheng, K Shi - Nonlinear Analysis: Hybrid …, 2019 - Elsevier
This paper addresses the problem of extended dissipativity-based resilient state estimation for discrete-time switched neural networks in the presence of unreliable links. To overcome …
N Yang, Y Yu, S Zhong, X Wang, K Shi, J Cai - Neural Networks, 2020 - Elsevier
This paper investigates the exponential synchronization issue of stochastic delayed memristive neural networks (SDMNNs) via a novel hybrid control (HC), where impulsive …
S Dong, S Zhong, K Shi, W Kang, J Cheng - Neurocomputing, 2019 - Elsevier
This work investigates the non-fragile H∞ state estimation issue for static neural networks (SNNs) with mixed time-varing delays and randomly occurring uncertainties (ROUs). ROUs …