Consensus in multi-agent systems means that reach an agreement among states of the whole ***,almost all the existed works on consensus have been in the description of the states of nodes,and fewer efforts have been de...
详细信息
ISBN:
(纸本)9781479947249
Consensus in multi-agent systems means that reach an agreement among states of the whole ***,almost all the existed works on consensus have been in the description of the states of nodes,and fewer efforts have been devoted to the consensus taking place on the edges of multi-agent *** this paper,we focus on the dynamics proceed on the edges and establish a discrete-time and a continuous-time edge consensus protocols respectively for directed multi-agent *** mapping the edge topology to its line graph of the original nodal topology,we analyze the consensus of the edge protocols rigorously,and get that both the discrete-time protocol and the continuous-time protocol of directed multi-agent systems can guarantee that an edge consensus is asymptotically reached for all initial states when the original directed system is strongly *** simulations are provided to show the effectiveness of both the discrete-time and the continuous-time models.
The property of changing resistance according to applied currents of memristors makes them candidates for emulating synapses in artificial neural networks. In this paper, we introduce a memristive synapse design into ...
详细信息
ISBN:
(纸本)9781479914821
The property of changing resistance according to applied currents of memristors makes them candidates for emulating synapses in artificial neural networks. In this paper, we introduce a memristive synapse design into neural network circuits. Combined with modified integrate-and-fire (I&F) complementary metal-oxide-semiconducter (CMOS) neurons, the memristive neural network shows similarities to its biological counterpart, in respect of biologically realistic, current-controlled spikes and adaptive synaptic plasticity. Then, the spike-rate-dependent plasticity (SRDP) of the synapse, an extended protocol of the Hebbian learning rule, is originally implemented by the circuit. And some advanced neural activities including learning, associative memory and forgetting are realized based on the SRDP rule. These activities are comprehensively validated on a neural network circuit inspired by famous Pavlov's dog-experiment with simulations and quantitative analyses.
As a sociological phenomenon, rumor spreading has been widely researched by sociologists and other fields’ scholars. How do people generate those strange thinking about the rumor? This paper, from artificial intellig...
详细信息
In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valu...
In this paper, we study the existence, uniqueness and stability of periodic solution for a wide class of memristor-based neural networks with time-varying delays. By employing the topological degree theory in set-valued analysis, differential inclusions theory and a new Lyapunov function method, we prove that the neural network has a unique periodic solution, which is globally exponentially stable. Moreover, we prove the existence, uniqueness and global exponential stability of equilibrium point for time-varying delayed memristor-based neural networks with constant coefficients. The obtained results improve and extend previous works on memristor-based or usual neural network dynamical systems with continuous or discontinuous right-hand side. Finally, two numerical examples are provided to show the applicability and effectiveness of our main results.
This paper presents a simple but effective sentence-length informed method to select informative sentences for active learning (AL) based SMT. A length factor is introduced to penalize short sentences to balance the &...
详细信息
This paper is concerned with the exponential synchronization problem of coupled memristive neural networks. In contrast to general neural networks, memristive neural networks exhibit state-dependent switching behavior...
详细信息
This paper is concerned with the exponential synchronization problem of coupled memristive neural networks. In contrast to general neural networks, memristive neural networks exhibit state-dependent switching behaviors due to the physical properties of memristors. Under a mild topology condition, it is proved that a small fraction of controlled sub- systems can efficiently synchronize the coupled systems. The pinned subsystems are identified via a search algorithm. Moreover, the information exchange network needs not to be undirected or strongly connected. Finally, two numerical simulations are performed to verify the usefulness and effectiveness of our results.
This paper addresses the problem of adaptive pinning synchronization of complex dynamical networks with nonlinear delayed intrinsic dynamics and time-varying delays. By introducing decentralized adaptive strategies to...
详细信息
The discrete-time double-integrator consensus and rendezvous problems are both addressed for distributed multiagent systems with directed switching topologies and input *** develop model predictive control algorithms ...
详细信息
ISBN:
(纸本)9781479947249
The discrete-time double-integrator consensus and rendezvous problems are both addressed for distributed multiagent systems with directed switching topologies and input *** develop model predictive control algorithms to achieve stable consensus or rendezvous provided that the proximity nets always have a directed spanning tree and the sampling period is sufficiently ***,the control horizon is extended to larger than one as well,which endows sufficient degrees of freedom to facilitate controller *** simulations are finally conducted to show the effectiveness of the control algorithms.
An approach of direct adaptive fuzzy sliding-mode control which combines the fuzzy control with the sliding-mode control, is proposed for the control of a class of unknown nonlinear dynamic systems. The control goal i...
详细信息
ISBN:
(纸本)9781479987313
An approach of direct adaptive fuzzy sliding-mode control which combines the fuzzy control with the sliding-mode control, is proposed for the control of a class of unknown nonlinear dynamic systems. The control goal is to obtain a direct adaptive fuzzy sliding-mode control law and a constructive Lyapunov synthesis approach with respect to a class of nonlinear systems without the knowledge of uncertainties. For improving the approximate performance of the fuzzy system, the proposed approach in this study not only online updates the parameter values in the consequence fuzzy sets, but also updates the shape parameters of the membership functions of the prime fuzzy sets. The fuzzy control rules are updated through the online adaptive learning, which makes the output of fuzzy control to approximate to a sliding-mode equivalent control. The asymptotic stability of the overall system based on Lyapunov theory is proved. Some numerical simulation results show the efficiency of the proposed approach.
Spiking neural （SN） P systems are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes. In this work, we investigate reversibility in SN P systems, as well as ...
详细信息
Spiking neural （SN） P systems are a class of distributed parallel computing devices inspired by the way neurons communicate by means of spikes. In this work, we investigate reversibility in SN P systems, as well as the computing power of reversible SN P systems. Reversible SN P systems are proved to have Turing creativity, that is, they can compute any recursively enumerable set of non-negative integers by simulating universal reversible register machine.
暂无评论