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Search Results: 1 - 10 of 305633 matches for " br>于洪洁 "
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Controlling chaos using time-delay nonlinear feedback
延迟-非线性反馈控制混沌

Yu Hong-Jie,<br>
物理学报 , 2005,
Abstract: A method of chaos control using time-delay nonlinear feedback based on stability criterion is proposed. By a suitable separation of the chaotic system, a special nonlinear function is obtained. We use the difference of nonlinear functions of the chaotic output signal and its delayed output signal to construct a continuous feedback input perturbation. The method can stabilize chaotic systems to a desired periodic orbit without using any external force. The method retains the advantages of performing the self-control via delayed feedback control method. Besides, the validity of control is ensured due to the stability criterion. The control can be started at any moment, and it is convenient and flexible. The coupled Duffing oscillator is given as numerical examples. The results of numerical simulation show the validity of the method.
Synchronization of star-network of hyperchaotic R?ssler systems
超混沌R?ssler系统构成的星形网络的混沌同步

Qin Jie,Yu Hong-Jie,<br>秦 ,
物理学报 , 2007,
Abstract: 通过对超混沌系统线性项与非线性项的适当分离配置,构造一个特殊的非线性耦合函数作为单元之间的耦合函数,提出非线性非对称耦合混沌同步方法,研究超混沌Rssler系统单元按照星形连接形式组成网络的同步问题.发现耦合强度在某一区域里存在着稳定的混沌同步现象.分析并讨论了不同参数在耦合过程中对混沌同步过程及其稳定性的影响.数值模拟结果证实该方法的有效性.
Chaotic control of the Hindmarsh-Rose neuron model
Hindmarsh-Rose神经模型的混沌控制

YU Hong-jie,PENG Jian-hua,<br>,彭建华
生物物理学报 , 2005,
Abstract: A method of chaos control based on stability criterion was applied to control chaotic spike trains and chaotic bursting of individual Hindmarsh-Rose neuron model. The chaotic orbit was stabilized on 5spikes/burst orbit embedded in the chaotic attractor by an input of the nonlinear time-continuous feedback perturbation to membrane potential. The numerical simulation showed that this method was effective on controlling Hindmarsh-Rose neuron model.
The Chaotic Synchronization of Hindmarsh-Rose Neural Networks
Hindmarsh-Rose 神经网络的混沌同步

YU Hong-Jie,LIN Chen,<br>,林晨
生物物理学报 , 2006,
Abstract: The chaotic synchronizations of neural networks linked by a nonlinear coupling function were discussed.The method was an expansion of SC method of chaotic synchronization based on the stability criterion.The evolutional equation of the difference was provided for calculating the synchronization stability.The stable chaotic synchronization could be achieved without calculation of the maximum conditional Lyapunov exponent when the coupling strength was taken as reference value.H-R neural network according to all-to-all form are treated as numerical example.It was shown that the stability region of coupling strength of numerous coupling neurons for achieving chaotic synchronization each other could be expected from estimating stability region of two coupling neurons only.Besides,the authors found that with increasing of the number of the coupled neurons,the coupling strength of satisfying stability equation of synchronization decreased.In order to achieve synchronization of a great deal coupling neurons in a network,we only need very low coupling strength.This method is still robust for chaotic synchronization even if with the influence of noise.
Associative memory and segmentation in the neural system under stimulation of stochastic or chaotic perceptual singals
神经系统中随机和混沌感知信号的联想记忆与分割

Peng Jian-Hua,Yu Hong-Jie,<br>彭建华,
物理学报 , 2007,
Abstract: We present in this paper some results on the temporal segmentation and retrieval of stored memories or patterns using neural networks composed of spiking neurons.Respecting the working environment,we present the network with stochastic or chaotic stimuli as their extremely working conditions and also with noise.We attempt to give an explanation to the function of memory retrieval of the brain system,where the stimuli usually may not be constant,sinusoidal or periodic,but rather chaotic or stochastic.For an input pattern which is a superposition of several stored patterns,it is shown that the proposed neuronal network model is capable of segmenting out each pattern one after another as synchronous firings of a subgroup of neurons,and if a corrupted input pattern is presented,the network is shown to be able to retrieve the perfect one,that is it has the function of associative memory.By thorougly adjusting the parameters,such as the coupling strength and the intensity of the noise,the temporal segmentation attains its optimal performance at intermediate noise intensity,which reminds of the stochastic resonance observed in the coupled spiking neuronal networks.
Synchronization of symmetrically nonlinear-coupled chaotic systems
对称非线性耦合混沌系统的同步

Yu Hong-Jie,Liu Yan-Zhu,<br>,刘延柱
物理学报 , 2005,
Abstract: 研究两个对称非线性耦合混沌系统的同步问题.通过对系统线性项与非线性项的适当分离, 构造一个特殊的非线性耦合项,发现在耦合强度α=05附近的某一区域里存在稳定的 混沌同步现象.提供判断同步误差稳定性的方程,利用线性系统的稳定性分析准则和条件Lya punov指数来检验同步状态的稳定性.新方法适用于连续时间系统的混沌同步,也适用于具有 两个(或多于两个)正Lyapunov指数的超混沌系统.以Lorenz系统,超混沌Rssler 系统作 为算例,数值模拟结果证实所提新方法的有效性.
Controlling chaos using half period delay-nonlinear feedback
半周期延迟-非线性反馈控制混沌

Yu Hong-Jie,Zheng Ning,<br>,郑宁
物理学报 , 2007,
Abstract: A method of chaos control using half period delayed-nonlinear feedback based on stability criterion is proposed in present paper. By a suitable separation of chaotic system, a special nonlinear function is obtained. Using the sum of nonlinear function about the chaotic output signal and its half period delayed output signal a continuous feedback input perturbation is constructed. Self-symmetric directly unstable periodic orbits can be stabilized by the method without using any external force. The method retains the advantages of performing the self-control of delay feedback control and overcomes its limitations. Beside, the validity of control is ensured due to the stability criterion. The control can be started at any moment, and it is convenient and flexible. The coupled coupling Duffing oscillator is taken as a numerical example. The results of numerical simulation show the validity of the method.
Chaotic control of Hindmarsh-Rose neuron by delayed self-feedback
延迟自反馈控制Hindmarsh-Rose神经元的混沌运动

Yu Hong-Jie,Tong Wei-Jun,<br>,童伟君
物理学报 , 2009,
Abstract: The control problems of chaotic dynamical patterns of single Hindmarsh-Rose neuron model are studied by using delayed feedback self-control method. Taking gain factor and time delay as controlling parameters respectively, in some ranges of the combination of gain factor and time-delay, we find that the chaotic burst pattern of inter-spike interval sequences of H-R neuron can be controlled to a single_spike period, double_spikes period, 3_or 4_spikes period pattern or multi-period of these patterns for inter-spike interval as the results of numerical simulation analysis. Choice of delay is in-dependent and doesn't rely on the period of unstable periodic orbits embedded within chaotic attractor. The chaotic burst orbit will be controlled to a certain type of periodic patterns of inter-spike interval automatically.
柔性转子-动态油膜轴承系统的分叉与混沌
,吕和祥
力学学报 , 2002,
Abstract:
柔性转子-动态油膜轴承系统的分叉与混沌
,吕和祥
力学学报 , 2002, DOI: 10.6052/0459-1879-2002-5-2001-225
Abstract:
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