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中文摘要：
提出了连续时间系统二维（不）稳定流形的一种新数值算法,不但可以快速地求得流形的直观图像,而且能够准确地获取流形上各点的位置、时间、轨道距离等丰富的信息,从而有利于人们从几何上去研究系统的全局行为,如边界特征、演化过程、奇异环等等.本算法首先通过解初值问题求出均匀分布的相邻轨道,然后连接这些轨道既得流形面.Lorenz系统原点的稳定流形的计算表明本算法快速有效.此外,通过试着寻找异宿轨道,还研究了一个三维神经网络中的混沌产生机理.
英文摘要：
This paper proposes a new algorithm for computing two-dimensional （un）stable manifolds in time continuous systems. With this algorithm, one can not only get a picture of a manifold efficiently, but also has many information of its every point, which are very useful for investigating the global dynamics of a system geometrically, such as features of stability region, evolution of the system flow and so on. The algorithm is mainly by finding many well distributed trajectories by solving initial value problems. An example on Lorenz system suggests this algorithm is very convenient. In addition, we study the chaotic dynamic of a three-dimensional neural network by detecting a heteroclinic orbit.
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