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 decision through self synchronizing sensor networks in the presence of propagation delays and nonreciprocal channels"
  Abstract: In this paper we propose and analyze a distributed algorithm for achieving globally optimal decisions, either estimation or detection, through a self-synchronization mechanism among linearly coupled integrators initialized with local measurements. We model the interaction among the nodes as a directed graph with weights (possibly) dependent on the radio channels, and we pose special attention to the effect of the propagation delay occurring in the exchange of data among sensors, as a function of the network geometry. We derive necessary and sufficient conditions for the proposed system to reach a consensus on globally optimal decision statistics. One of the major results proved in this work is that a consensus is reached with exponential convergence speed for any bounded delay condition if and only if the directed graph is quasi-strongly connected. We provide a closed form expression for the global consensus, showing that the effect of delays is, in general, the introduction of a bias in the final decision. Finally, we exploit our closed form expression to devise a double-step consensus mechanism able to provide an unbiased estimate with minimum extra complexity, without the need to know or estimate the channel parameters.

Connected through hyperedge HE-1 (induced by source paper "distributed inference for relay assisted sensor networks with intermittent measurements over fading channels"):
  with members:
    - "toward resource optimal consensus over the wireless medium"
    - "convergence rate analysis of distributed gossip linear parameter estimation fundamental limits and tradeoffs"
    - "the role of persistent graphs in the agreement seeking of social networks"
    - "distributed parameter estimation in sensor networks nonlinear observation models and imperfect communication"
    - "sensor networks with random links topology design for distributed consensus"

Connected through hyperedge HE-2 (induced by source paper "distributed detection and estimation in wireless sensor networks"):
  with members:
    - "gossip algorithms for distributed signal processing"
    - "energy scaling laws for distributed inference in random fusion networks"
    - "detection of gauss markov random fields with nearest neighbor dependency"
    - "distributed parameter estimation in sensor networks nonlinear observation models and imperfect communication"
    - "decentralized maximum likelihood estimation for sensor networks composed of nonlinearly coupled dynamical systems"

Connected through hyperedge HE-3 (induced by source paper "distributed estimation and control of algebraic connectivity over random graphs"):
  with members:
    - "distributed detection and estimation in wireless sensor networks"
    - "sensor networks with random links topology design for distributed consensus"
    - "distributed consensus algorithms in sensor networks quantized data and random link failures"

Connected through hyperedge HE-4 (induced by source paper "joint sensing and power allocation in nonconvex cognitive radio games nash equilibria and distributed algorithms"):
  with members:
    - "real and complex monotone communication games"
    - "joint sensing and power allocation in nonconvex cognitive radio games quasi nash equilibria"
    - "game theory and the frequency selective interference channel"
    - "optimal multiband joint detection for spectrum sensing in cognitive radio networks"
    - "optimal linear precoding strategies for wideband noncooperative systems based on game theory part i nash equilibria"

Connected through hyperedge HE-5 (induced by source paper "distributed consensus over wireless sensor networks affected by multipath fading"):
  with members:
    - "decentralized maximum likelihood estimation for sensor networks composed of nonlinearly coupled dynamical 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.IT(Information Theory)