论文标题
使用傅立叶功能对库普曼操作员的在线估算
Online Estimation of the Koopman Operator Using Fourier Features
论文作者
论文摘要
转移操作员提供线性表示和非线性动力学系统的全球性，物理意义的特征。发现转移操作员，例如Koopman操作员，需要仔细制作的可观察到的词典，并在动态系统的状态下作用。这是临时的，需要完整的数据集进行评估。在本文中，我们提供了一个优化方案，以允许与在线数据共同学习可观察到的和库普曼操作员。我们的结果表明，我们能够重建演变并代表复杂动力学系统的全局特征。
Transfer operators offer linear representations and global, physically meaningful features of nonlinear dynamical systems. Discovering transfer operators, such as the Koopman operator, require careful crafted dictionaries of observables, acting on states of the dynamical system. This is ad hoc and requires the full dataset for evaluation. In this paper, we offer an optimization scheme to allow joint learning of the observables and Koopman operator with online data. Our results show we are able to reconstruct the evolution and represent the global features of complex dynamical systems.
