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 "distortion bounds for source broadcast over degraded channel"):
  Abstract: The joint source-channel coding problem of sending a memoryless source over a memoryless degraded broadcast channel is considered here. We derive an inner bound and two outer bounds on the achievable distortion region. Moreover, when specialized to Gaussian source broadcast or binary source broadcast, the inner bound and outer bounds could recover the best known inner bound and outer bound. Besides, we also extend the inner bound and outer bounds to Wyner-Ziv source broadcast problem, i.e., source broadcast with degraded side information available at decoders. We obtain some new bounds when specialized to Wyner-Ziv Gaussian source broadcast and Wyner-Ziv binary source broadcast.

Includes members:
  Member "a source channel separation theorem with application to the source broadcast problem":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "low density majority codes and the problem of graceful degradation")
  Member "comments on approximate characterizations for the gaussian source broadcast distortion region":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "distortion bounds for source broadcast problem")
  Member "outer bounds on the admissible source region for broadcast channels with correlated sources":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "a lower bound on the expected distortion of joint source channel coding")
  Member "hybrid coding an interface for joint source channel coding and network communication":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "the likelihood encoder for lossy compression")
  Member "achievability proof via output statistics of random binning":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "biometric and physical identifiers with correlated noise for controllable private authentication")
  Member "hybrid digital analog codes for source channel broadcast of gaussian sources over gaussian channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "joint state estimation and communication over a state dependent gaussian multiple access channel")
  Member "the achievable distortion region of bivariate gaussian source on gaussian broadcast channel":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "hybrid coding an interface for joint source channel coding and network communication")
  Member "on the capacity of the discrete memoryless broadcast channel with feedback":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "exploiting location information to enhance throughput in downlink v2i systems")

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.IT(Information Theory)