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: "infinite horizon optimal transmission power control for remote state estimation over fading channels"
  Abstract: Jointly optimal transmission power control and remote estimation over an infinite horizon is studied. A sensor observes a dynamic process and sends its observations to a remote estimator over a wireless fading channel characterized by a time-homogeneous Markov chain. The successful transmission probability depends on both the channel gains and the transmission power used by the sensor. The transmission power control rule and the remote estimator should be jointly designed, aiming to minimize an infinite-horizon cost consisting of the power usage and the remote estimation error. A first question one may ask is: Does this joint optimization problem have a solution? We formulate the joint optimization problem as an average cost belief-state Markov decision process and answer the question by proving that there exists an optimal deterministic and stationary policy. We then show that when the monitored dynamic process is scalar, the optimal remote estimates depend only on the most recently received sensor observation, and the optimal transmission power is symmetric and monotonically increasing with respect to the innovation error.

Connected through hyperedge HE-1 (induced by source paper "optimal causal rate constrained sampling of the wiener process"):
  with members:
    - "remote estimation of the wiener process over a channel with random delay"
    - "event triggered stabilization of linear systems under bounded bit rates"
    - "the distortion rate function of sampled wiener processes"
    - "rate cost tradeoffs in control"
    - "optimal estimation via nonanticipative rate distortion function and applications to time varying gauss markov processes"
    - "event triggered control under time varying rates and channel blackouts"
    - "optimal estimation with limited measurements and noisy communication"
    - "optimal strategies for communication and remote estimation with an energy harvesting sensor"

Connected through hyperedge HE-2 (induced by source paper "optimal scheduling of multiple sensors over lossy and bandwidth limited channels"):
  with members:
    - "opportunistic scheduling as restless bandits"
    - "attack allocation on remote state estimation in multi systems structural results and asymptotic solution"
    - "optimal dynamic multicast scheduling for cache enabled content centric wireless networks"
    - "sensor scheduling in variance based event triggered estimation with packet drops"
    - "stochastic event triggered sensor scheduling for remote state estimation"
    - "optimal strategies for communication and remote estimation with an energy harvesting sensor"

Connected through hyperedge HE-3 (induced by source paper "remote estimation over a packet drop channel with markovian state"):
  with members:
    - "on remote estimation with multiple communication channels"
    - "decentralized stochastic control with partial history sharing a common information approach"
    - "optimal strategies for communication and remote estimation with an energy harvesting sensor"

Connected through hyperedge HE-4 (induced by source paper "consistent distributed state estimation with global observability over sensor network"):
  with members:
    - "partition based distributed kalman filter with plug and play features"
    - "distributing the kalman filter for large scale systems"

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)