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: "the capacity region of the degraded finite state broadcast channel"
  Abstract: We consider the discrete, time-varying broadcast channel with memory under the assumption that the channel states belong to a set of finite cardinality. We first define the physically degraded finite-state broadcast channel for which we derive the capacity region. We then define the stochastically degraded finite-state broadcast channel and derive the capacity region for this scenario as well. In both scenarios we consider the non-indecomposable finite-state channel as well as the indecomposable one.

Connected through hyperedge HE-1 (induced by source paper "the secrecy capacity of gaussian mimo channels with finite memory full version"):
  with members:
    - "on the capacity of narrowband plc channels"
    - "principles of physical layer security in multiuser wireless networks a survey"
    - "full rank solutions for the mimo gaussian wiretap channel with an average power constraint"
    - "source channel coding theorems for the multiple access relay channel"
    - "private broadcasting over independent parallel channels"
    - "for the grid and through the grid the role of power line communications in the smart grid"
    - "secured communication over frequency selective fading channels a practical vandermonde precoding"
    - "towards the secrecy capacity of the gaussian mimo wire tap channel the 2 2 1 channel"

Connected through hyperedge HE-2 (induced by source paper "estimating the directed information and testing for causality"):
  with members:
    - "a characterization of the minimal average data rate that guarantees a given closed loop performance level"
    - "information networks with in block memory"
    - "universal estimation of directed information"
    - "detection and isolation of link failures under the agreement protocol"
    - "the relation between granger causality and directed information theory a review"
    - "directed information causal estimation and communication in continuous time"
    - "interpretations of directed information in portfolio theory data compression and hypothesis testing"
    - "feedback capacity of the compound channel"

Connected through hyperedge HE-3 (induced by source paper "capacity and coding for the ising channel with feedback"):
  with members:
    - "to feed or not to feed back"
    - "feedback capacity of the compound channel"
    - "a coding theorem for a class of stationary channels with feedback"
    - "finite state channels with time invariant deterministic feedback"
    - "the capacity of channels with feedback"
    - "feedback capacity of the first order moving average gaussian channel"

Connected through hyperedge HE-4 (induced by source paper "interpretations of directed information in portfolio theory data compression and hypothesis testing"):
  with members:
    - "directed information causal estimation and communication in continuous time"
    - "feedback capacity of the compound channel"
    - "a coding theorem for a class of stationary channels with feedback"
    - "achieving the gaussian rate distortion function by prediction"
    - "finite state channels with time invariant deterministic feedback"
    - "the capacity of channels with feedback"

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)