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: "event based state estimation an emulation based approach"
  Abstract: An event-based state estimation approach for reducing communication in a networked control system is proposed. Multiple distributed sensor agents observe a dynamic process and sporadically transmit their measurements to estimator agents over a shared bus network. Local event-triggering protocols ensure that data is transmitted only when necessary to meet a desired estimation accuracy. The event-based design is shown to emulate the performance of a centralised state observer design up to guaranteed bounds, but with reduced communication. The stability results for state estimation are extended to the distributed control system that results when the local estimates are used for feedback control. Results from numerical simulations and hardware experiments illustrate the effectiveness of the proposed approach in reducing network communication.

Connected through hyperedge HE-1 (induced by source paper "resource aware iot control saving communication through predictive triggering"):
  with members:
    - "feedback control goes wireless guaranteed stability over low power multi hop networks"
    - "distributed event based state estimation for networked systems an lmi approach"
    - "virtual vs real trading off simulations and physical experiments in reinforcement learning with bayesian optimization"
    - "predictive and self triggering for event based state estimation"
    - "sensor scheduling in variance based event triggered estimation with packet drops"
    - "cyber physical control of road freight transport"
    - "internet of things iot a vision architectural elements and future directions"

Connected through hyperedge HE-2 (induced by source paper "event triggered learning"):
  with members:
    - "resource aware iot control saving communication through predictive triggering"
    - "stochastic event triggered sensor scheduling for remote state estimation"

Connected through hyperedge HE-3 (induced by source paper "evaluating low power wireless cyber physical systems"):
  with members:
    - "event triggered learning for resource efficient networked control"
    - "wireless network design for control systems a survey"
    - "virtual vs real trading off simulations and physical experiments in reinforcement learning with bayesian optimization"

Connected through hyperedge HE-4 (induced by source paper "event triggered learning for resource efficient networked control"):
  with members:
    - "distributed event based state estimation for networked systems an lmi approach"

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)