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 "finite field matrix channels for network coding"):
  Abstract: In 2010, Silva, Kschischang and K\"otter studied certain classes of finite field matrix channels in order to model random linear network coding where exactly $t$ random errors are introduced. #R##N#In this paper we consider a generalisation of these matrix channels where the number of errors is not required to be constant, indeed the number of errors may follow any distribution. We show that a capacity-achieving input distribution can always be taken to have a very restricted form (the distribution should be uniform given the rank of the input matrix). This result complements, and is inspired by, a paper of Nobrega, Silva and Uchoa-Filho, that establishes a similar result for a class of matrix channels that model network coding with link erasures. Our result shows that the capacity of our channels can be expressed as a maximisation over probability distributions on the set of possible ranks of input matrices: a set of linear rather than exponential size.

Includes members:
  Member "on the capacity of multiplicative finite field matrix channels":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "communication over finite chain ring matrix channels")
  Member "communication over finite field matrix channels":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "ranksign an efficient signature algorithm based on the rank metric")
  Member "a rank metric approach to error control in random network coding":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "roos bound for skew cyclic codes in hamming and rank metric")
  Member "bounds on covering codes with the rank metric":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "construction and covering properties of constant dimension codes")
  Member "coding for errors and erasures in random network coding":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "on the gap between scalar and vector solutions of generalized combination networks")
  Member "packing and covering properties of rank metric codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "multiple rate channel codes in texttt gf p n 2")

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)