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: "spatially coupled repeat accumulate codes"
  Abstract: In this paper we propose a new class of spatially coupled codes based on repeat-accumulate protographs. We show that spatially coupled repeat-accumulate codes have several advantages over spatially coupled low-density parity-check codes including simpler encoders and slightly higher code rates than spatially coupled low-density parity-check codes with similar thresholds and decoding complexity (as measured by the Tanner graph edge density).

Connected through hyperedge HE-1 (induced by source paper "design of irregular sc ldpc codes with non uniform degree distributions by linear programing"):
  with members:
    - "on the design of fast convergent ldpc codes for the bec an optimization approach"
    - "spatially coupled ldpc codes constructed from protographs"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "spatially coupled sparse codes on graphs theory and practice"
    - "on the convergence speed of spatially coupled ldpc ensembles"
    - "a simple proof of threshold saturation for coupled scalar recursions"
    - "spatially coupled ensembles universally achieve capacity under belief propagation"
    - "threshold saturation via spatial coupling why convolutional ldpc ensembles perform so well over the bec"

Connected through hyperedge HE-2 (induced by source paper "continuous transmission of spatially coupled ldpc code chains"):
  with members:
    - "spatially coupled ldpc codes constructed from protographs"
    - "triggering wave like convergence of tail biting spatially coupled ldpc codes"
    - "triggering wave like convergence of tail biting spatially coupled ldpc codes single and dual channel setup"
    - "a scaling law to predict the finite length performance of spatially coupled ldpc codes"
    - "threshold saturation for spatially coupled ldpc and ldgm codes on bms channels"
    - "terminated and tailbiting spatially coupled codes with optimized bit mappings for spectrally efficient fiber optical systems"
    - "on the convergence speed of spatially coupled ldpc ensembles"
    - "new codes on graphs constructed by connecting spatially coupled chains"

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)