摘要
利用状态观测器理论提出了具有多个非线性项的混沌系统的标量输出同步方法。通过对误差系统的变换,以降低非线性项对误差系统的影响,从而可减少极点配置参数。基于这种方法,设计出含有多个非线性项的Hopfield型混沌神经网络的同步系统,并计算出同步参数,从而实现了含有多个非线性项的混沌系统同步,并用计算机仿真证实了此方法的有效性。Hopfield型混沌神经网络具有全局吸引的混沌吸引子,混沌性能稳定,采用线性电路器件容易实现,对混沌的实际应用有参考价值。
This paper proposes an observer-based method to design synchronization systems for the chaotic systems containing multiple nonlinear parts by a scalar output. By a transform on the error system, the dynamical effect from the nonlinear parts is reduced, and therefore the number of parameters for pole assignment is decreased. This method was successfully applied to the synchronization of the 3D Hopfield neural network which has three nonlinear parts. Computer simulation shows that the synchronization error becomes zero very fast, which suggests that the method is effective. Since the Hopfieldtype chaotic neural network has a global attractive attractor, this work may be used in practical application of chaos.
出处
《重庆邮电大学学报(自然科学版)》
北大核心
2009年第1期123-126,共4页
Journal of Chongqing University of Posts and Telecommunications(Natural Science Edition)
基金
重庆市教委科学技术研究项目(KJ080515)
重庆市自然科学基金计划资助项目(CSTC
2008BB2409)
重庆邮电大学青年基金(A2008-26)