This paper presents an adaptive neural network (NN) sliding mode control for synchronization of inhibitory coupled Hindmarsh-Rose (HR) neurons. A single HR neuron may exhibit spike-burst chaotic behaviors. Inhibitory ...
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This paper presents an adaptive neural network (NN) sliding mode control for synchronization of inhibitory coupled Hindmarsh-Rose (HR) neurons. A single HR neuron may exhibit spike-burst chaotic behaviors. Inhibitory coupling makes two HR neurons behaves in anti-phase quasi-synchronization mode. We first derive the sliding mode controller via active control strategy. Then, a simple radial basis function (RBF) NN is designed to approximate the uncertain nonlinear part of the error dynamical system which has been assumed to be available in the active control. The weights of the NN are tuned on-line based on the sliding mode reaching law. According to the Lyapunov stability theory, the stability of the closed-loop error system is guaranteed. Synchronization is obtained by proper choice of the control parameters. The simulation results demonstrate the effectiveness of the proposed control method.
Weak electrical coupling connections are ubiquitous in neuronal system. In this paper, we examine the effect of time delays on the synchronization properties of the weakly coupled neuronal oscillators by means of phas...
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Weak electrical coupling connections are ubiquitous in neuronal system. In this paper, we examine the effect of time delays on the synchronization properties of the weakly coupled neuronal oscillators by means of phase-model reduction. The bifurcation analysis clarifies how the time delays affect the existence and stability of in-phase, anti-phase and out of phase synchronization states. The results show that time delay can promote synchronization in an efficient way.
To overcome challenges of processing timeliness and changeful topics when analyzing opinions of online news comments, free-tagging methods including two steps, object identification and polarity analysis, are proposed...
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Pulse gas metal arc welding (pulse GMAW) plays an important role in advanced manufacturing technology, and it is transforming the conventional welding process into fine controllable one. However, the development of so...
Pulse gas metal arc welding (pulse GMAW) plays an important role in advanced manufacturing technology, and it is transforming the conventional welding process into fine controllable one. However, the development of sophisticated pulse GMAW machines becomes very complex. The synergic parameters preset are needed in order to achieve optimum weld process. In addition, there are many facets of disturbances and adaptive process control is necessary to maintain optimum state. This paper reviews progress in control of pulse GMAW technology and summarize control strategies for embedded digital system detailedly.
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