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: "a novel approach to the statistical modeling of wireline channels"
  Abstract: We report here that channel power gain and Root-Mean-Square Delay Spread (RMS-DS) in Low/Medium Voltage power line channels are negatively correlated lognormal random variables. Further analysis of other wireline channels allows us to report a strong similarity between some properties observed in power line channels and the ones observed in other wireline channels, e.g. coaxial cables and phone lines. For example, it is here reported that channel power gain and logarithm of the RMS-DS in DSL links are \textit{linearly} correlated random variables. Exploiting these results, we here propose a statistical wireline channel model where tap amplitudes and delays are generated in order to reflect these physical properties. Although wireline channels are considered deterministic as their impulse response can be readily calculated once the link topology is known, a statistical wireline channel model is useful because the variability of link topologies and wiring practices give rise to a stochastic aspect of wireline communications that has not been well characterized in the literature. Finally, we also point out that alternative channel models that normalize impulse responses to a common (often unitary) power gain may be misleading when assessing the performance of equalization schemes since this normalization artificially removes the correlation between channel power gain and RMS-DS and, thus, Inter-Symbol Interference (ISI).

Connected through hyperedge HE-1 (induced by source paper "on the capacity of mimo broadband power line communications channels"):
  with members:
    - "state of the art in power line communications from the applications to the medium"
    - "on the capacity of narrowband plc channels"

Connected through hyperedge HE-2 (induced by source paper "state of the art in power line communications from the applications to the medium"):
  with members:
    - "on efficiency and validity of previous homeplug mac performance analysis"
    - "for the grid and through the grid the role of power line communications in the smart grid"

Connected through hyperedge HE-3 (induced by source paper "for the grid and through the grid the role of power line communications in the smart grid"):
  with members:
    - "discrete time block models for transmission line channels static and doubly selective cases"

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)