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: "spectral shape of doubly generalized ldpc codes efficient and exact evaluation"
  Abstract: This paper analyzes the asymptotic exponent of the weight spectrum for irregular doubly-generalized LDPC (D-GLDPC) codes. In the process, an efficient numerical technique for its evaluation is presented, involving the solution of a 4 × 4 system of polynomial equations. The expression is consistent with previous results, including the case where the normalized weight or stopping set size tends to zero. The spectral shape is shown to admit a particularly simple form in the special case where all variable nodes are repetition codes of the same degree, a case which includes Tanner codes; for this case it is also shown how certain symmetry properties of the local weight distribution at the CNs induce a symmetry in the overall weight spectral shape function. Finally, using these new results, weight and stopping set size spectral shapes are evaluated for some example generalized and doubly-generalized LDPC code ensembles.

Connected through hyperedge HE-1 (induced by source paper "a probabilistic peeling decoder to efficiently analyze generalized ldpc codes over the bec"):
  with members:
    - "design of ldpc code ensembles with fast convergence properties"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "on the minimum distance of generalized spatially coupled ldpc codes"
    - "approaching capacity at high rates with iterative hard decision decoding"
    - "maxwell construction the hidden bridge between iterative and maximum a posteriori decoding"
    - "finite length scaling for iteratively decoded ldpc ensembles"

Connected through hyperedge HE-2 (induced by source paper "design of ldpc code ensembles with fast convergence properties"):
  with members:
    - "minimum distance distribution of irregular generalized ldpc code ensembles"

Connected through hyperedge HE-3 (induced by source paper "minimum distance distribution of irregular generalized ldpc code ensembles"):
  with members:
    - "on the growth rate of the weight distribution of irregular doubly generalized ldpc codes"
    - "weight distribution and decoding of codes on hypergraphs"

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)