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 "stopping set distributions of some linear codes"):
  Abstract: Stopping sets and stopping set distribution of an low-density parity-check code are used to determine the performance of this code under iterative decoding over a binary erasure channel (BEC). Let $C$ be a binary $[n,k]$ linear code with parity-check matrix $H$, where the rows of $H$ may be dependent. A stopping set $S$ of $C$ with parity-check matrix $H$ is a subset of column indices of $H$ such that the restriction of $H$ to $S$ does not contain a row of weight one. The stopping set distribution $\{T_i(H)\}_{i=0}^n$ enumerates the number of stopping sets with size $i$ of $C$ with parity-check matrix $H$. Note that stopping sets and stopping set distribution are related to the parity-check matrix $H$ of $C$. Let $H^{*}$ be the parity-check matrix of $C$ which is formed by all the non-zero codewords of its dual code $C^{\perp}$. A parity-check matrix $H$ is called BEC-optimal if $T_i(H)=T_i(H^*), i=0,1,..., n$ and $H$ has the smallest number of rows. On the BEC, iterative decoder of $C$ with BEC-optimal parity-check matrix is an optimal decoder with much lower decoding complexity than the exhaustive decoder. In this paper, we study stopping sets, stopping set distributions and BEC-optimal parity-check matrices of binary linear codes. Using finite geometry in combinatorics, we obtain BEC-optimal parity-check matrices and then determine the stopping set distributions for the Simplex codes, the Hamming codes, the first order Reed-Muller codes and the extended Hamming codes.

Includes members:
  Member "single exclusion number and the stopping redundancy of mds codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "new two stage automorphism group decoders for cyclic codes in the erasure channel")
  Member "permutation decoding and the stopping redundancy hierarchy of cyclic and extended cyclic codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "stopping redundancy hierarchy beyond the minimum distance")
  Member "on the asymptotic weight and stopping set distribution of regular ldpc ensembles":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "the approximate maximum likelihood certificate")
  Member "results on parity check matrices with optimal stopping and or dead end set enumerators":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "bounds on separating redundancy of linear codes and rates of x codes")
  Member "complete enumeration of stopping sets of full rank parity check matrices of hamming codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "fountain uncorrectable sets and finite length analysis")
  Member "on the stopping distance and the stopping redundancy of codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "decoder tailored polar code design using the genetic algorithm")
  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)