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: "distributed observers for lti systems"
  Abstract: We consider the problem of distributed state estimation of a linear time-invariant (LTI) system by a network of sensors. We develop a distributed observer that guarantees asymptotic reconstruction of the state for the most general class of LTI systems, sensor network topologies and sensor measurement structures. Our analysis builds upon the following key observation - a given node can reconstruct a portion of the state solely by using its own measurements and constructing appropriate Luenberger observers; hence it only needs to exchange information with neighbors (via consensus dynamics) for estimating the portion of the state that is not locally detectable. This intuitive approach leads to a new class of distributed observers with several appealing features. Furthermore, by imposing additional constraints on the system dynamics and network topology, we show that it is possible to construct a simpler version of the proposed distributed observer that achieves the same objective while admitting a fully distributed design phase. Our general framework allows extensions to time-varying networks that result from communication losses, and scenarios including faults or attacks at the nodes.

Connected through hyperedge HE-1 (induced by source paper "a new approach for distributed hypothesis testing with extensions to byzantine resilience"):
  with members:
    - "byzantine resilient distributed observers for lti systems"
    - "defending non bayesian learning against adversarial attacks"
    - "distributed optimization under adversarial nodes"
    - "exponentially fast parameter estimation in networks using distributed dual averaging"
    - "matrix representation of iterative approximate byzantine consensus in directed graphs"
    - "iterative approximate byzantine consensus in arbitrary directed graphs"

Connected through hyperedge HE-2 (induced by source paper "a distributed observer for a discrete time linear system"):
  with members:
    - "a distributed observer for a time invariant linear system"
    - "a hybrid observer for a distributed linear system with a changing neighbor graph"
    - "a distributed algorithm for solving a linear algebraic equation"

Connected through hyperedge HE-3 (induced by source paper "bias estimation in sensor networks"):
  with members:
    - "controlling rigid formations of mobile agents under inconsistent measurements"
    - "network flows that solve linear equations"
    - "robust decentralized state estimation and tracking for power systems via network gossiping"

Connected through hyperedge HE-4 (induced by source paper "detection and mitigation of biasing attacks on distributed estimation networks"):
  with members:
    - "byzantine resilient distributed observers for lti systems"
    - "controller jammer game models of denial of service in control systems operating over packet dropping links"
    - "detection of biasing attacks on distributed estimation networks"
    - "gain scheduled synchronization of parameter varying systems via relative h consensus with application to synchronization of uncertain bilinear systems"
    - "detectability of distributed consensus based observer networks an elementary analysis and extensions"
    - "on the genericity properties in distributed estimation topology design and sensor placement"
    - "conditions for detectability in distributed consensus based observer networks"

Connected through hyperedge HE-5 (induced by source paper "byzantine resilient distributed observers for lti systems"):
  with members:
    - "a distributed observer for a time invariant linear system"
    - "secure distributed state estimation of an lti system over time varying networks and analog erasure channels"
    - "detection and mitigation of biasing attacks on distributed estimation networks"
    - "detection of biasing attacks on distributed estimation networks"
    - "iterative approximate byzantine consensus in arbitrary directed graphs"
    - "distributing the kalman filter for large scale systems"

Connected through hyperedge HE-6 (induced by source paper "finite time distributed state estimation over time varying graphs exploiting the age of information"):
  with members:
    - "a distributed observer for a time invariant linear system"
    - "byzantine resilient distributed observers for lti systems"
    - "a hybrid observer for a distributed linear system with a changing neighbor graph"
    - "a distributed algorithm for solving a linear algebraic equation"
    - "conditions for detectability in distributed consensus based observer networks"

Connected through hyperedge HE-7 (induced by source paper "secure distributed state estimation of an lti system over time varying networks and analog erasure channels"):
  with members:
    - "a distributed observer for a time invariant linear system"
    - "resilient consensus of second order agent networks asynchronous update rules with delays"
    - "detection of biasing attacks on distributed estimation networks"
    - "byzantine multi agent optimization part ii"
    - "iterative approximate byzantine consensus in arbitrary directed graphs"

Connected through hyperedge HE-8 (induced by source paper "a hybrid observer for a distributed linear system with a changing neighbor graph"):
  with members:
    - "a distributed algorithm for solving a linear algebraic equation"

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)