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: "joint successive cancellation decoding of polar codes over intersymbol interference channels"
  Abstract: Polar codes are a class of capacity-achieving codes for the binary-input discrete memoryless channels (B-DMCs). However, when applied in channels with intersymbol interference (ISI), the codes may perform poorly with BCJR equalization and conventional decoding methods. To deal with the ISI problem, in this paper a new joint successive cancellation (SC) decoding algorithm is proposed for polar codes in ISI channels, which combines the equalization and conventional decoding. The initialization information of the decoding method is the likelihood functions of ISI codeword symbols rather than the codeword symbols. The decoding adopts recursion formulas like conventional SC decoding and is without iterations. This is in contrast to the conventional iterative algorithm which performs iterations between the equalizer and decoder. In addition, the proposed SC trellis decoding can be easily extended to list decoding which can further improve the performance. Simulation shows that the proposed scheme significantly outperforms the conventional decoding schemes in ISI channels.

Connected through hyperedge HE-1 (induced by source paper "list decoding of universal polar codes"):
  with members:
    - "polar codes for the deletion channel weak and strong polarization"
    - "universal polarization for processes with memory"
    - "performance bounds of concatenated polar coding schemes"
    - "soft decision decoding of reed muller codes recursive lists"
    - "fast polarization for processes with memory"
    - "polar coding for processes with memory"
    - "polar codes with dynamic frozen symbols and their decoding by directed search"
    - "universal polar codes"

Connected through hyperedge HE-2 (induced by source paper "polar codes for the deletion channel weak and strong polarization"):
  with members:
    - "universal polarization for processes with memory"
    - "capacity upper bounds for deletion type channels"
    - "a simple proof of fast polarization"
    - "fast polarization for processes with memory"
    - "polar coding for the binary erasure channel with deletions"
    - "polar coding for processes with memory"
    - "list decoding of polar codes"
    - "polar codes characterization of exponent bounds and constructions"

Connected through hyperedge HE-3 (induced by source paper "universal polarization for processes with memory"):
  with members:
    - "a simple proof of fast polarization"
    - "fast polarization for processes with memory"
    - "polar coding for processes with memory"
    - "construction of polar codes for arbitrary discrete memoryless channels"
    - "on the construction of polar codes for channels with moderate input alphabet sizes"
    - "universal polar codes for more capable and less noisy channels and sources"
    - "universal source polarization and an application to a multi user problem"
    - "channel upgradation for non binary input alphabets and macs"

Connected through hyperedge HE-4 (induced by source paper "fast polarization for processes with memory"):
  with members:
    - "a simple proof of fast polarization"
    - "polar codes with a stepped boundary"
    - "polar coding for processes with memory"
    - "achieving the secrecy capacity of wiretap channels using polar codes"
    - "polar codes are optimal for lossy source coding"
    - "polarization for arbitrary discrete memoryless channels"
    - "on the rate of channel polarization"

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)