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: "linear system identification in a nonlinear setting nonparametric analysis of the nonlinear distortions and their impact on the best linear approximation"
  Abstract: Linear system identification [1]?[4] is a basic step in modern control design approaches. Starting from experimental data, a linear dynamic time-invariant model is identified to describe the relationship between the reference signal and the output of the system. At the same time, the power spectrum of the unmodeled disturbances is identified to generate uncertainty bounds on the estimated model.

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"
    - "data driven nonlinear identification of li ion battery based on a frequency domain nonparametric analysis"
    - "regularized nonparametric volterra kernel estimation"
    - "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 "the use of machine learning and big five personality taxonomy to predict construction workers safety behaviour"):
  with members:
    - "an immersive virtual reality serious game to enhance earthquake behavioral responses and post earthquake evacuation preparedness in buildings"
    - "the effectiveness of traditional tools and computer aided technologies for health and safety training in the construction sector a systematic review"
    - "immersive virtual reality serious games for evacuation training and research a systematic literature review"
    - "cached sufficient statistics for efficient machine learning with large datasets"

Connected through hyperedge HE-3 (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:
    - "data driven nonlinear identification of li ion battery based on a frequency domain nonparametric analysis"

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)