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 low complexity decoding of product codes for high throughput fiber optic systems"
  Abstract: We study low-complexity iterative decoding algorithms for product codes. We revisit two algorithms recently proposed by the authors based on bounded distance decoding (BDD) of the component codes that improve the performance of conventional iterative BDD (iBDD). We then propose a novel decoding algorithm that is based on generalized minimum distance decoding of the component codes. The proposed algorithm closes over 50% of the performance gap between iBDD and turbo product decoding (TPD) based on the Chase-Pyndiah algorithm. Moreover, the algorithm only leads to a limited increase in complexity with respect to iBDD and has significantly lower complexity than TPD. The studied algorithms are particularly interesting for high-throughput fiber-optic communications.

Connected through hyperedge HE-1 (induced by source paper "on product codes with probabilistic amplitude shaping for high throughput fiber optic systems"):
  with members:
    - "binary message passing decoding of product codes based on generalized minimum distance decoding"
    - "binary message passing decoding of product like codes"
    - "iterative bounded distance decoding of product codes with scaled reliability"
    - "energy efficient soft assisted product decoders"
    - "increasing achievable information rates via geometric shaping"
    - "achievable rates for probabilistic shaping"
    - "miscorrection free decoding of staircase codes"
    - "probabilistic amplitude shaping with hard decision decoding and staircase codes"

Connected through hyperedge HE-2 (induced by source paper "binary message passing decoding of product like codes"):
  with members:
    - "binary message passing decoding of product codes based on generalized minimum distance decoding"
    - "low complexity concatenated ldpc staircase codes"
    - "iterative bounded distance decoding of product codes with scaled reliability"
    - "energy efficient soft assisted product decoders"
    - "probabilistic amplitude shaping with hard decision decoding and staircase codes"
    - "achievable information rates for coded modulation with hard decision decoding for coherent fiber optic systems"
    - "density evolution for deterministic generalized product codes on the binary erasure channel at high rates"
    - "staircase codes fec for 100 gb s otn"

Connected through hyperedge HE-3 (induced by source paper "binary message passing decoding of product codes based on generalized minimum distance decoding"):
  with members:
    - "binary message passing decoding of product like codes"
    - "iterative bounded distance decoding of product codes with scaled reliability"
    - "energy efficient soft assisted product decoders"
    - "density evolution for deterministic generalized product codes on the binary erasure channel at high rates"
    - "staircase codes fec for 100 gb s otn"
    - "approaching capacity at high rates with iterative hard decision decoding"
    - "analysis and design of binary message passing decoders"

Connected through hyperedge HE-4 (induced by source paper "a novel soft aided bit marking decoder for product codes"):
  with members:
    - "iterative bounded distance decoding of product codes with scaled reliability"
    - "energy efficient soft assisted product decoders"
    - "staircase codes fec for 100 gb s otn"

Connected through hyperedge HE-5 (induced by source paper "energy efficient soft assisted product decoders"):
  with members:
    - "a 588 gb s ldpc decoder based on finite alphabet message passing"
    - "analysis and design of binary message passing decoders"

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)