Author
Yanxi Chen
Bio: Yanxi Chen is an academic researcher from Chongqing Jiaotong University. The author has contributed to research in topics: Matrix (mathematics) & Quaternion. The author has an hindex of 1, co-authored 1 publications receiving 22 citations.
Papers
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TL;DR: Both delay-independent and delay-dependent criteria to guarantee the existence, uniqueness and global stability of equilibrium point for the considered FOQVNNs are derived in the form of linear matrix inequality (LMI).
72 citations
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TL;DR: In this paper , the global Mittag-Leffler projective synchronization (GM-LPS) on fractional-order quaternion-valued neural networks (FOQVNNs) including mixed delays and impulses is simultaneously explored.
32 citations
TL;DR: A LMI criterion guaranteeing the global asymptotic stability of the proposed FOCVNNs is deduced by constructing suitable Lyapunov-Krasovskii functional and utilizing inequality technique.
22 citations
TL;DR: Several delay-independent and delay-dependent criteria are established to make sure that the equilibrium point of the addressed FOCVPNNs is existent, unique and globally robustly stable.
19 citations
TL;DR: In this article , a proportional-integral-type estimator design problem is studied for recurrent neural networks under the encoding-decoding communication mechanism, and a sufficient condition is obtained for the existence of the desired estimator and the parameters of the estimator are obtained by solving certain matrix inequality.
Abstract: In this paper, the proportional–integral-type estimator design problem is studied for recurrent neural networks under the encoding–decoding communication mechanism. In the process of the measurement data transmission, an encoding–decoding mechanism is introduced to improve the security of the network by encrypting the measurement data. The purpose of this paper is to design a proportional–integral-type estimation algorithm such that the estimation error dynamics is exponentially ultimately bounded in mean square. First, a sufficient condition is obtained for the existence of the desired estimator. Then, the parameters of the estimator are obtained by solving certain matrix inequality. Finally, a simulation example is given to verify the effectiveness of the designed estimation algorithm.
18 citations
TL;DR: In this paper, the synchronization problem for a class of coupled neural networks with impulsive control, where the saturation structure of impulse action is fully considered, has been studied and a sufficient condition for exponential synchronization problem is obtained by replacing saturation nonlinearity with a dead-zone function.
16 citations