human: Given a hyperedge-centered hypergraph: <hypergraph>, where the center hyperedge is induced by one source paper and its member nodes are the cited papers.

Details of the hypergraph:
Center hyperedge (induced by source paper "online output feedback parameter and state estimation for second order linear systems"):
  Abstract: A concurrent learning based adaptive observer is developed in this paper for a class of second-order linear time-invariant systems with uncertain system matrices. The developed technique yields an exponentially convergent state estimator and an exponentially convergent parameter estimator. As opposed to persistent excitation required for parameter convergence in traditional adaptive methods, excitation over a finite time-interval is sufficient for the developed technique to achieve exponential convergence.

Includes members:
  Member "concurrent learning for parameter estimation using dynamic state derivative estimators":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "simultaneous state and parameter estimation for second order nonlinear systems")
  Member "efficient model based reinforcement learning for approximate online optimal control":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "output feedback online optimal control for a class of nonlinear systems")
  Member "model based reinforcement learning for approximate optimal regulation":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "output feedback online optimal control for a class of nonlinear systems")
  Member "concurrent learning based approximate feedback nash equilibrium solution of n player nonzero sum differential games":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "model based reinforcement learning for infinite horizon approximate optimal tracking")

Question: Please tell me which class the source paper 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)