通过广义融合套索惩罚联合稀疏最小二乘法识别非线性动力系统

IF 5.2 2区工程技术 Q1 ENGINEERING, MECHANICAL

Nonlinear Dynamics Pub Date : 2023-12-12 DOI:10.1007/s11071-023-09098-y

Yisha Lu, Wei Xu, Lizhi Niu, Wenting Zhang, Minjuan Yuan

引用次数: 0

摘要

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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Joint sparse least squares via generalized fused lasso penalty for identifying nonlinear dynamical systems

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来源期刊

Nonlinear Dynamics 工程技术-工程：机械

CiteScore

9.00

自引率

17.90%

发文量

966

审稿时长

5.9 months

期刊介绍： Nonlinear Dynamics provides a forum for the rapid publication of original research in the field. The journal’s scope encompasses all nonlinear dynamic phenomena associated with mechanical, structural, civil, aeronautical, ocean, electrical, and control systems. Review articles and original contributions are based on analytical, computational, and experimental methods. The journal examines such topics as perturbation and computational methods, symbolic manipulation, dynamic stability, local and global methods, bifurcations, chaos, and deterministic and random vibrations. The journal also investigates Lie groups, multibody dynamics, robotics, fluid-solid interactions, system modeling and identification, friction and damping models, signal analysis, and measurement techniques.