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: "on generalized minimum distance decoding thresholds for the awgn channel"
  Abstract: We consider the Additive White Gaussian Noise channel with Binary Phase Shift Keying modulation. Our aim is to enable an algebraic hard decision Bounded Minimum Distance decoder for a binary block code to exploit soft information obtained from the demodulator. This idea goes back to Forney and is based on treating received symbols with low reliability as erasures. This erasing at the decoder is done using a threshold, each received symbol with reliability falling below the threshold is erased. Depending on the target overall complexity of the decoder this pseudo-soft decision decoding can be extended from one threshold T to z>1 thresholds T_1 1 thresholds case, starting with a geometric interpretation of the optimal threshold location problem and using an approach from Zyablov.

Connected through hyperedge HE-1 (induced by source paper "optimal threshold based multi trial error erasure decoding with the guruswami sudan algorithm"):
  with members:
    - "on multiple decoding attempts for reed solomon codes a rate distortion approach"
    - "optimal thresholds for gmd decoding with l 1 over l extended bounded distance decoders"
    - "decoding generalized concatenated codes using interleaved reed solomon codes"

Connected through hyperedge HE-2 (induced by source paper "optimal thresholds for gmd decoding with l 1 over l extended bounded distance decoders"):
  with members:
    - "decoding generalized concatenated codes using interleaved reed solomon codes"
    - "collaborative decoding of interleaved reed solomon codes and concatenated code designs"

Connected through hyperedge HE-3 (induced by source paper "adaptive single trial error erasure decoding for binary codes"):
  with members:
    - "optimal thresholds for gmd decoding with l 1 over l extended bounded distance decoders"
    - "decoding generalized concatenated codes using interleaved reed solomon codes"

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)