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: "decoder error probability of mrd codes"
  Abstract: In this paper, we first introduce the concept of elementary linear subspace, which has similar properties to those of a set of coordinates. Using this new concept, we derive properties of maximum rank distance (MRD) codes that parallel those of maximum distance separable (MDS) codes. Using these properties, we show that the decoder error probability of MRD codes with error correction capability t decreases exponentially with t^2 based on the assumption that all errors with the same rank are equally likely. We argue that the channel based on this assumption is an approximation of a channel corrupted by crisscross errors.

Connected through hyperedge HE-1 (induced by source paper "packing and covering properties of rank metric codes"):
  with members:
    - "constant rank codes"
    - "a rank metric approach to error control in random network coding"
    - "constant rank codes and their connection to constant dimension codes"
    - "properties of codes in rank metric"
    - "properties of codes with the rank metric"

Connected through hyperedge HE-2 (induced by source paper "properties of rank metric codes"):
  with members:
    - "properties of codes in rank metric"
    - "properties of codes with the rank metric"
    - "properties of subspace subcodes of optimum codes in rank metric"

Connected through hyperedge HE-3 (induced by source paper "macwilliams identity for codes with the rank metric"):
  with members:
    - "properties of codes in rank metric"
    - "properties of codes with the rank metric"

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)