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 "improved bit flipping algorithm for successive cancellation decoding of polar codes"):
  Abstract: The interest in polar codes has been increasing significantly since their adoption for use in the 5$^{\rm th}$ generation wireless systems standard. Successive cancellation (SC) decoding algorithm has low implementation complexity, but yields mediocre error-correction performance at the code lengths of interest. SC-Flip algorithm improves the error-correction performance of SC by identifying possibly erroneous decisions made by SC and re-iterates after flipping one bit. It was recently shown that only a portion of bit-channels are most likely to be in error. In this work, we investigate the average log-likelihood ratio (LLR) values and their distribution related to the erroneous bit-channels, and develop the Thresholded SC-Flip (TSCF) decoding algorithm. We also replace the LLR selection and sorting of SC-Flip with a comparator to reduce the implementation complexity. Simulation results demonstrate that for practical code lengths and a wide range of rates, TSCF shows negligible loss compared to the error-correction performance obtained when all single-errors are corrected. At matching maximum iterations, TSCF has an error-correction performance gain of up to $0.45$ dB compared with SC-Flip decoding. At matching error-correction performance, the computational complexity of TSCF is reduced by up to $40\%$ on average, and requires up to $5\times$ lower maximum number of iterations.

Includes members:
  Member "partitioned successive cancellation flip decoding of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-1 (induced by source paper "deep learning aided successive cancellation decoding of polar codes")
  Member "improved successive cancellation flip decoding of polar codes based on error distribution":
    also connected through other hyperedges:
      - Hyperedge HE-2 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "dynamic scflip decoding of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-3 (induced by source paper "polar codes and their quantum domain counterparts")
  Member "an improved scflip decoder for polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-4 (induced by source paper "shifted pruning for list decoding of polar codes")
  Member "partitioned list decoding of polar codes analysis and improvement of finite length performance":
    also connected through other hyperedges:
      - Hyperedge HE-5 (induced by source paper "sublinear latency for simplified successive cancellation decoding of polar codes")
  Member "polarbear a 28 nm fd soi asic for decoding of polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-6 (induced by source paper "ternary quantized polar code decoders analysis and design")
  Member "on error correction performance and implementation of polar code list decoders for 5g":
    also connected through other hyperedges:
      - Hyperedge HE-7 (induced by source paper "general strong polarization")
  Member "fast and flexible successive cancellation list decoders for polar codes":
    also connected through other hyperedges:
      - Hyperedge HE-8 (induced by source paper "polar codes and their quantum domain counterparts")

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)