J
Jinde Cao
Researcher at Southeast University
Publications - 1590
Citations - 72167
Jinde Cao is an academic researcher from Southeast University. The author has contributed to research in topics: Artificial neural network & Exponential stability. The author has an hindex of 117, co-authored 1430 publications receiving 57881 citations. Previous affiliations of Jinde Cao include Yunnan University & Columbia University.
Papers
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Brief paper: A unified synchronization criterion for impulsive dynamical networks
TL;DR: A unified synchronization criterion is derived for directed impulsive dynamical networks by proposing a concept named ''average impulsive interval'' which is theoretically and numerically proved to be less conservative than existing results.
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Second-order leader-following consensus of nonlinear multi-agent systems via pinning control
TL;DR: This paper addresses what kind of agents and how many agents should be pinned, and establishes some sufficient conditions to guarantee that all agents asymptotically follow the virtual leader.
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Global asymptotic stability of a general class of recurrent neural networks with time-varying delays
Jinde Cao,Jun Wang +1 more
TL;DR: Several new sufficient conditions for ascertaining the existence, uniqueness, and global asymptotic stability of the equilibrium point of such recurrent neural networks are obtained by using the theory of topological degree and properties of nonsingular M-matrix, and constructing suitable Lyapunov functionals.
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Global asymptotic and robust stability of recurrent neural networks with time delays
Jinde Cao,Jun Wang +1 more
TL;DR: Several sufficient conditions are derived for the existence, uniqueness, and GRS of equilibria for interval neural networks with time delays by use of a new Lyapunov function and matrix inequality.
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Brief paper: Second-order consensus in multi-agent dynamical systems with sampled position data
TL;DR: It is found that second-order consensus in such a multi-agent system cannot be reached without any sampled position data under the given protocol while it can be achieved by appropriately choosing the sampling period.