摘要
提出一种基于径向基函数 (RBF)神经网络的动力系统Lyapunov指数计算方法 ,设计了一个RBF网络结构 ,推导了基于RBF网络的Lyapunov指数计算公式 .仿真实验表明 ,与其它现有方法相比 ,此方法计算精度较高 ,收敛速度较快 ,而且只需要较少的样本数据量 .本方法能更准确、更快速地计算动力系统的Lya punov指数 .
An algorithm for computing Lyapunov exponents of a dynamical system based on radial basis function(RBF) neural networks is proposed. An RBF network structure is designed. The formula of the Lyapunov exponents based on an RBF network is derived. Simulations show that compared with the other existing algorithms, the proposed algorithm has higher accuracy and convergence speed, and it needs much less observed samples. It is demonstrated that the proposed algorithm can compute the Lyapunov exponents of a dynamical system more accurately and rapidly.
出处
《信息与控制》
CSCD
北大核心
2004年第5期523-526,共4页
Information and Control
关键词
LYAPUNOV指数
RBF神经网络
动力系统辨识
非线性系统
Lyapunov exponents
RBF(radial basis function) neural networks
dynamical systems identification
nonlinear system
