A5101429077- stochastic dynamics and bifurcation
- Neural Networks Stability and Synchronization
- Advanced Memory and Neural Computing
- Neural dynamics and brain function
- Neural Networks and Applications
- Nonlinear Dynamics and Pattern Formation
- Chaos control and synchronization
- Neuroscience of respiration and sleep
- Stability and Controllability of Differential Equations
Guangdong Polytechnic Normal University
2020-2021
Henan Polytechnic University
2012-2020
Potsdam Institute for Climate Impact Research
2018
Humboldt-Universität zu Berlin
2018
Beihang University
2009-2012
Shanghai Normal University
2008
In this paper, by means of the invariance principle differential equations, an adaptive feedback scheme is proposed to realize desynchronization in synchronous multi-coupled chaotic neurons mix-adaptive effectively. Numerical simulations for Hindmarsh–Rose neural model with self-coupling are illustrated which agree well our theoretical analysis. It observed that strengths asymptotically converge a local fixed value finite time, especially linear coupling self-coupling. Furthermore,...
The pre-Bötzinger complex, which is located at a ventrolateral medulla of human and mammal, considered to be the center for generation respiratory rhythms. In normal state, rhythm uniform orderly. Otherwise, will change pathological state. Therefore, monitoring great significance in health. this paper, according two-coupled model complex with calcium ion current, we investigate transition mechanism anti-phase bursting synchronization by using phase-plane analysis, bifurcation fast-slow...
Based on the inequality analysis, matrix theory and spectral theory, a class of general periodic neural networks with delays impulses is studied. Some sufficient conditions are established for existence globally exponential stability unique solution. Furthermore, results applied to some typical impulsive network systems as special cases, real-life example show feasibility our results.
<p style='text-indent:20px;'>In this paper, the synchronization problem of complex-valued memristive competitive neural networks(CMCNNs) with different time scales is investigated. Based on differential inclusions and inequality techniques, some novel sufficient conditions are derived to ensure drive-response systems by designing a proper controller. Finally, numerical example provided illustrate usefulness feasibility our results.</p>
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The memristor as the fourth circuit element, it can capture some key aspects of biological synaptic plasticity. So, is significant that characteristic memristors considered in neural networks. This paper investigates input-to-state stability (ISS) a class memristive simplified Cohen–Grossberg bidirectional associative memory (BAM) networks with variable time delays. In sense Filippov solution, novel sufficient criteria for ISS are obtained based on differential inclusions and inequalities;...