human: Given a node-centered hypergraph: <hypergraph>, where nodes represent papers and hyperedges represent sets of papers co-cited by a source paper.

Details of the hypergraph:
Center node: "data driven nonlinear identification of li ion battery based on a frequency domain nonparametric analysis"
  Abstract: Lithium ion batteries are attracting significant and growing interest, because their high energy and high power density render them an excellent option for energy storage, particularly in hybrid and electric vehicles. In this brief, a data-driven polynomial nonlinear state-space model is proposed for the operating points at the cusp of linear and nonlinear regimes of the battery’s electrical operation, based on the thorough nonparametric frequency domain characterization and quantification of the battery’s behavior in terms of its linear and nonlinear behavior at different levels of the state of charge.

Connected through hyperedge HE-1 (induced by source paper "nonlinear system identification a user oriented roadmap"):
  with members:
    - "extending the best linear approximation framework to the process noise case"
    - "regularized nonparametric volterra kernel estimation"
    - "linear system identification in a nonlinear setting nonparametric analysis of the nonlinear distortions and their impact on the best linear approximation"
    - "using the best linear approximation with varying excitation signals for nonlinear system characterization"
    - "grey box nonlinear state space modelling for mechanical vibrations identification"
    - "parametric identification of parallel wiener hammerstein systems"

Connected through hyperedge HE-2 (induced by source paper "a local polynomial approach to nonparametric estimation of the best linear approximation of lithium ion battery from multiple datasets"):
  with members:
    - "linear system identification in a nonlinear setting nonparametric analysis of the nonlinear distortions and their impact on the best linear approximation"

Question: Please tell me which class the center node belongs to. The 40 classes are: cs.NA(Numerical Analysis), cs.MM(Multimedia), cs.LO(Logic in Computer Science), cs.CY(Computers and Society), cs.CR(Cryptography and Security), cs.DC(Distributed, Parallel, and Cluster Computing), cs.HC(Human-Computer Interaction), cs.CE(Computational Engineering, Finance, and Science), cs.NI(Networking and Internet Architecture), cs.CC(Computational Complexity), cs.AI(Artificial Intelligence), cs.MA(Multiagent Systems), cs.GL(General Literature), cs.NE(Neural and Evolutionary Computing), cs.SC(Symbolic Computation), cs.AR(Hardware Architecture), cs.CV(Computer Vision and Pattern Recognition), cs.GR(Graphics), cs.ET(Emerging Technologies), cs.SY(Systems and Control), cs.CG(Computational Geometry), cs.OH(Other Computer Science), cs.PL(Programming Languages), cs.SE(Software Engineering), cs.LG(Machine Learning), cs.SD(Sound), cs.SI(Social and Information Networks), cs.RO(Robotics), cs.IT(Information Theory), cs.PF(Performance), cs.CL(Computation and Language), cs.IR(Information Retrieval), cs.MS(Mathematical Software), cs.FL(Formal Languages and Automata Theory), cs.DS(Data Structures and Algorithms), cs.OS(Operating Systems), cs.GT(Computer Science and Game Theory), cs.DB(Databases), cs.DL(Digital Libraries), cs.DM(Discrete Mathematics). Directly output the class name.

gpt: cs.SY(Systems and Control)