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 "statistical learning aided list decoding of semi random block oriented convolutional codes"):
  Abstract: In this paper, we propose a statistical learning aided list decoding algorithm, which integrates a serial list Viterbi algorithm~(SLVA) with a soft check instead of the conventional cyclic redundancy check~(CRC), for semi-random block oriented convolutional codes~(SRBO-CCs). The basic idea is that, compared with an erroneous candidate codeword, the correct candidate codeword for the first sub-frame has less effect on the output of Viterbi algorithm~(VA) for the second sub-frame. The threshold for testing the correctness of the candidate codeword is then determined by learning the statistical behavior of the introduced empirical divergence function~(EDF). With statistical learning aided list decoding, the performance-complexity tradeoff and the performance-delay tradeoff can be achieved by adjusting the statistical threshold and extending the decoding window, respectively. To analyze the performance, a closed-form upper bound and a simulated lower bound are derived. Simulation results verify our analysis and show that: 1) The statistical learning aided list decoding outperforms the sequential decoding in high signal-to-noise ratio~(SNR) region; 2) under the constraint of equivalent decoding delay, the SRBO-CCs have comparable performance with the polar codes.

Includes members:
  Member "decoding reed muller and polar codes by successive factor graph permutations":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "perm2vec graph permutation selection for decoding of error correction codes using self attention")
  Member "performance analysis of block markov superposition transmission of short codes":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "statistical learning aided decoding of bmst of tail biting convolutional code")
  Member "a new class of multiple rate codes based on block markov superposition transmission":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "systematic block markov superposition transmission of repetition codes")
  Member "block markov superposition transmission construction of big convolutional codes from short codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "compressed coding amp based decoding and analog spatial coupling")
  Member "list decoding of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "channel polarization a method for constructing capacity achieving codes for symmetric binary input memoryless channels":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "reed muller codes theory and algorithms")

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)