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 "structural cost optimal design of sensor networks for distributed estimation"):
  Abstract: In this letter, we discuss cost optimization of sensor networks monitoring structurally full-rank systems under distributed observability constraint. Using structured systems theory, the problem is relaxed into two subproblems: first, sensing cost optimization; and second, networking cost optimization. Both problems are reformulated as combinatorial optimization problems. The sensing cost optimization is shown to have a polynomial-order solution. The networking cost optimization is shown to be NP-hard in general, but has a polynomial-order solution under specific conditions. A 2-approximation polynomial-order relaxation is provided for general networking cost optimization, which is applicable in large-scale system monitoring.

Includes members:
  Member "distributed estimation recovery under sensor failure":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "on the controllability of clustered scale free networks")
  Member "measurement partitioning and observational equivalence in state estimation":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the controllability of clustered scale free networks")
  Member "graph theoretic distributed inference in social networks":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "on the controllability of clustered scale free networks")
  Member "on the genericity properties in distributed estimation topology design and sensor placement":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "on the controllability of clustered scale free networks")
  Member "diffusion strategies outperform consensus strategies for distributed estimation over adaptive networks":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "decentralized multi agent reinforcement learning with networked agents recent advances")

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)