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 "on the pseudocodeword redundancy of binary linear codes"):
  Abstract: The AWGNC, BSC, and max-fractional pseudocodeword redundancies of a binary linear code are defined to be the smallest number of rows in a parity-check matrix such that the corresponding minimum pseudoweight is equal to the minimum Hamming distance of the code. It is shown that most codes do not have a finite pseudocodeword redundancy. Also, upper bounds on the pseudocodeword redundancy for some families of codes, including codes based on designs, are provided. The pseudocodeword redundancies for all codes of small length (at most 9) are computed. Furthermore, comprehensive results are provided on the cases of cyclic codes of length at most 250 for which the eigenvalue bound of Vontobel and Koetter is sharp.

Includes members:
  Member "the trapping redundancy of linear block codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "performance bounds and estimates for quantized ldpc decoders")
  Member "a decomposition theory for binary linear codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "on the number of circuits in regular matroids with connections to lattices and codes")
  Member "pseudo codeword analysis of tanner graphs from projective and euclidean planes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "pseudocodeword free criterion for codes with cycle free tanner graph")
  Member "bounds on the threshold of linear programming decoding":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "impact of redundant checks on the lp decoding thresholds of ldpc codes")
  Member "on the stopping distance and the stopping redundancy of codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "decoder tailored polar code design using the genetic algorithm")
  Member "graph cover decoding and finite length analysis of message passing iterative decoding of ldpc codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "efficient qp admm decoder for binary ldpc codes and its performance analysis")
  Member "improved upper bounds on stopping redundancy":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "bounds on separating redundancy of linear codes and rates of x codes")

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)